{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#all_slow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "from fastai.vision.all import *\n",
    "from fastai.text.all import *\n",
    "from fastai.collab import *\n",
    "from fastai.tabular.all import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# fastai applications - quick start"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "fastai's applications all use the same basic steps and code:\n",
    "\n",
    "- Create appropriate `DataLoaders`\n",
    "- Create a `Learner`\n",
    "- Call a *fit* method\n",
    "- Make predictions or view results.\n",
    "\n",
    "In this quick start, we'll show these steps for a wide range of difference applications and datasets. As you'll see, the code in each case is extremely similar, despite the very different models and data being used."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computer vision classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code below does the following things:\n",
    "\n",
    "1. A dataset called the [Oxford-IIIT Pet Dataset](http://www.robots.ox.ac.uk/~vgg/data/pets/) that contains 7,349 images of cats and dogs from 37 different breeds will be downloaded from the fast.ai datasets collection to the GPU server you are using, and will then be extracted.\n",
    "2. A *pretrained model* that has already been trained on 1.3 million images, using a competition-winning model will be downloaded from the internet.\n",
    "3. The pretrained model will be *fine-tuned* using the latest advances in transfer learning, to create a model that is specially customized for recognizing dogs and cats.\n",
    "\n",
    "The first two steps only need to be run once. If you run it again, it will use the dataset and model that have already been downloaded, rather than downloading them again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>error_rate</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.173790</td>\n",
       "      <td>0.018827</td>\n",
       "      <td>0.005413</td>\n",
       "      <td>00:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>error_rate</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.064295</td>\n",
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       "      <td>0.005413</td>\n",
       "      <td>00:14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = untar_data(URLs.PETS)/'images'\n",
    "\n",
    "def is_cat(x): return x[0].isupper()\n",
    "dls = ImageDataLoaders.from_name_func(\n",
    "    path, get_image_files(path), valid_pct=0.2, seed=42,\n",
    "    label_func=is_cat, item_tfms=Resize(224))\n",
    "\n",
    "learn = cnn_learner(dls, resnet34, metrics=error_rate)\n",
    "learn.fine_tune(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can do inference with your model with the `predict` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "PILImage mode=RGB size=197x250"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = PILImage.create('images/cat.jpg')\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Is this a cat?: True.\n",
      "Probability it's a cat: 0.999722\n"
     ]
    }
   ],
   "source": [
    "is_cat,_,probs = learn.predict(img)\n",
    "print(f\"Is this a cat?: {is_cat}.\")\n",
    "print(f\"Probability it's a cat: {probs[1].item():.6f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computer vision segmentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is how we can train a segmentation model with fastai, using a subset of the [*Camvid* dataset](http://www0.cs.ucl.ac.uk/staff/G.Brostow/papers/Brostow_2009-PRL.pdf):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2.882460</td>\n",
       "      <td>2.096923</td>\n",
       "      <td>00:03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1.602270</td>\n",
       "      <td>1.543582</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1.417732</td>\n",
       "      <td>1.225782</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1.307454</td>\n",
       "      <td>1.071090</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1.170338</td>\n",
       "      <td>0.884501</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1.047036</td>\n",
       "      <td>0.799820</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.947965</td>\n",
       "      <td>0.754801</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>0.868178</td>\n",
       "      <td>0.728161</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>0.804939</td>\n",
       "      <td>0.720942</td>\n",
       "      <td>00:02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = untar_data(URLs.CAMVID_TINY)\n",
    "dls = SegmentationDataLoaders.from_label_func(\n",
    "    path, bs=8, fnames = get_image_files(path/\"images\"),\n",
    "    label_func = lambda o: path/'labels'/f'{o.stem}_P{o.suffix}',\n",
    "    codes = np.loadtxt(path/'codes.txt', dtype=str)\n",
    ")\n",
    "\n",
    "learn = unet_learner(dls, resnet34)\n",
    "learn.fine_tune(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize how well it achieved its task, by asking the model to color-code each pixel of an image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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yTkywrKIQeu/oBve8W1lL3nu8dBYQA6ny/e9dI4eum3WWuqowbRstuVUMWFgNQnofBjmtNX18WSJBEQUSQgx4z3yxROl9fn7/J/FeMZ/V/K3pj7JfHVCOcjbyDb7b/9kk+feJul7yxVszPjg9oN5pMY3BtCHuXlcty3mFPWtZLBdsb9/iX5lrfP3emHNnz5Fl47W0YSVVh98PfzspeBw59al3PsMzH9thPqvxdpv9/RnlqGBjc4ML588lTt0n6rri1q2rd+XUK19+hsVyzvbWAb9x9eqJ4dQ9FYqIkGUhblqMp3hnaZuK+ewgDCSKUJQF2WjcWzZKr7JPlISBvrIo0UpHQfcrC4kVuVTMOrHGUvsaYy3OxViz98GtkxUJPeCdRSS4+Aziy8qpfpaNxHPkec6f/G3fSVUZ8iLjV+qf5HvOvQ+lWAWZE46Nallz68YOL730ScoiZ7Q5xowdWzv7WOfCAzJT/Nxom6vbV7hxcJPdvSUfuHiJt108z5fOHvUVvPF4HDn1/DveSvX0JWyR8eyrFe+efkbi1ANiuay5dXObn832KdWdOfXJl1/g6pUr3Lh5sjh1V4WiVJAekeCKCSBaU5Qj6qqOgq4YlSVZrsPhfNSk9RLVKrIsQ5TGOQv4mOXSCX5w3T0uuNcxJRHngix2v3sfBhezDAjhgd46GwSROyIBGNOiRFBag4fFMgwcX79xhbycMJExf/jq70edi0SFk2fOnlB0z4jwvFGU+YizZ8d465jPK5xzlEVGngmuXfLKpz/F3t4By2VIVb1+/QaTyYRGLpJn+QM/c4664Lezqk4aHndONaZlQydO3S/WxamX3/Menntx/5Fx6p6D8sHI6CwNjxKFaI3WGu9DDnqWZ8FS0h6fuRCvbdqQpWA0OstDIz1hQpUPKY50LvzwhN7jo1Uk/aWE2DHdv971A4Z+cIwuTRJCdoTvcvRFaNuW+XzOzZs32Dh1BmsN80XL6TMbaBUGwrzz0Vo7Rs8lIIBWmrIoGZUFdV0DjkxrRmVBkSm8admZz6hqgzEOEWF/f5+9vX3mxQZnTp3iYZ46D5IK+aiROJVwJwjycJxazHlY6X8YTt1VobRtG3LMtUJDPygoImitcE4FtzqmKHbvrXO0jcFai1JCXrRopeNvIf/dOof3FrxCaQUonA0utsR8hSO0CLnzKlpoQp+1Ym100X2YFCYiIY8/tikQ1VM3LZ965RWm0z02NjaYnT3N57294DNeXqJURtu2lOWot8gS7o4s1xRlRlnmVPWSxbxiWdVcOHuKPFeIeLw11LWhNa6/m8vlkq3tbV61jtOb7wHuP6f+dngz3LUngVN/YHHAeDROnHoA5Ll6KE698upl3iMXeVScuodCMUGwCTFWnYUJNfggcN3AIdDHd0VCrnqeaZREL9qDNSakOhLKQ1jnsMbSZi0qToxSWq1cLB+EvTs2dOGCINjGtP0EH51lYbaxDymRWZZRFMVqoJE++QVQGOuZHcyZz+fs7m3xq+Mxo9GY6WST9zYXGI1G99mNTy6MscwO5kynBWU5JdMj6mqB4HDO0xpL1bR4VhlNiLC/t8fPnBHeWVWMyvJQhtPjjCeBU/94c4tJ5NS7X2n4zHd/VuLUfeBhOPXSS59g+dZTj4xT9xyUv93EGe+7/JPO7hlG2sKs2izL0Fp1B8K51Yxb51ywnDxhMNA6nLUop8nzHBmkPXYpjViHdJO1IjFCbSON1kLVtqFdsYOHgu9iVosgfTvCxDDL7m7DfL6kyHM2NpYsJhOyLCPL7hkNfOKRaUVR5IzHE7IszHlo2zrM+JYw36JuDM4Bsgq3CJ6mbdnfn7G1vc2F8+eZjNeTndLhpNrDTxqnztxoeOtb35Y4dUzojlOjNyenjnGHY6x1mLcOQShlZUX1cdcYp83zrI+7OWtDiQlAidB2h4iudtu0WOPw1lPmwQqygWF9RgvQhwE8Ib8+fBdKETjnCKUfdJjc5Q4TQAR8dNuttSEk4D22cdRVgxKhrhpmZ89TFmUS/gH6B1GExHj8sx/f4tT+jJ3TG1h3wGK55GBxgFKCcx5jPVXdzVHgkAw5Y1i6Bb98puWrlkvGo/Fa4+yr5vq7bfaI8ORw6kMXRrxrNkucOoI7cUoUFEXG5uabk1P3zPJSSqEl1BOyxvSF4LqaRF1iiHUWYyw2Wj2hVEOIt1prUTb+FYUnVEt1HvI8R2fZynKLdYvwnizOIA7ZIitB7jpTJMwc9t6T5XksvOdpm1AdVUTI8ow8z6NrGGLYWWF7QnfUcs6xWCz5hadnvP38WX5X9VB9/1jBWsPBfI51Bq01WimapuaXNucclDPMrGa2N8PbVYR+WTVUdRtLhgzqT3nCfQK8c7z0wkt8wal3sLm5SZHna2uz9w5jDHVTc3ptR314PImc+tT+y3jnmE7f8Si6/ETidpx6+Z0bXL587URy6vJnn4+14gxNU/Mld9jurgplOp0AoU5QW1WgJFy8VmQ6w0kYFFoul1i/yiLRImiBLr9dZypaX6ESalYI1jqw3YxdHwcOY+kIT8yfjzFf3wm6RItJUZQjsixHKQ1x5q91Fm9dLDvhAIX3MX3yUJwhEinO+A0I6SxbW9tsbGyyIGM8njzx2Sneh/kmHxwvefXqK30WknWGxZU5xrQxswi0kpAKK1A3La2Nk/OGfR9TRbpuPTg44EZ9i/FkwrNPP/3AbbQ2KI9lVfORpxR1XVPbimW75Nv4vIfthrXhSeTUb1wQ9i8qLi4WiVOsOPXqp17lg6cXK07dMiwO1sOpX3+HZ+eC50v2HryNn373aeqmpqoqdl56KXCqrlhWS77ks2/P1Xt6KDbGR1sTUhadVVilg+vtY5G7usY6H2KvmUZ1Fztw3/E6ypePVU2DC9cP7kXTrBuUVGFnvPN9Pv2wXVmR9wOaXX0i77qBza6zfV+Mr3PV+/x4gjaH1SAoEqqo7u/vsy8l4/F49dsTCu9jbHa5z7Ur12lMjSeWAbGhrLmSUHsq0wqtgwXdGhf7Hg65yEfetm3LzmyHzc0Nnn7qEvdbRTVU5nXszWYsFgvmizlXgWq5pGlbmqa95zHeSCROJU71nNrb59p863Xh1Pb2DhsbGzj11INzan/GYjFnPl9wc2vrWJy6q0JZLBarhkZBtW2L9zXdWgqwKsddFAUqyxAf3N3gpsey196HF2EISXtwMQPF2lBfSKE6JuCEUNk0Vj+1zuK8jR3vyLOCLM9DE9og+MNBSe/DjXHW4p1D9WUtPO/f+lEAfs+ZPxKVu+9j1nVds7OzwwffOuHrfPj1SbaoTGswTQs4RtmYumpY1g1AH+Lw3kNVx5nZYQ6FqCw87AZ1o4h79Smk8fdfPWe5tlHzmaaNLvrxOjwMJDtmBxX/ym1T+TlN1mBuGKrGkmUF48mptfbHw+Jx5VQX/urnryRO3REdpy6/+yyjVxavC6eu37iB1pr26XP3xanLn3WeprUcHFR8+KMfoVrOQw245nicumdxSK2DO+wRiqLAtC3VcgldE0WhtDCdTClHo7CNtbGwXMhrV7KaceuiG22swbRNiPX23bKa8RtGG8Fjo8Y04EHpjDwPKXFKpI+VH7KiRBBUOIjEffH4WKbiq879UTxg2pqyKMINcp2bDrPZAa9evszs6fNMJtMQL35CUVU1B/MF82zJubPnMLZlvjig696uz5UourpPSkK64qH7OUBvYfkQua8WC7a3t/l375jxlfWpY8d9d/Z2mM1mfORSRn29paosxsJ08wwTnZPnBePRyap2+7hyyseyLcbaxKl74KXnp2xt1MxfPBmcuvzZ5/v3O7vbzGYH7OzuUVf3z6m7KpSwGlsIzmmlg/XiPTrTYZ0EH9Zo0FpTjkbkRRHy3z141+W7q44lvYttbVjgx1iL0jp+rWLWSGfBqOhKC4jtV43zg1FLnWnw3SQr6FNP4un6uK7zOPFAyFpZkS24+q4b+PIeL6GC7mKx5Oatm1x6KnsihN9ay2KxZGd3O8R04zyG+WzBwcEc9VTG2TNnaEzLwWKB9ZbWGJyxWGcIE6NjOir02UmddQwMjCTf/R8+OcdyueTKlau0p8bk3dyMAbyHpqlZ1hVVVTGbzbi1tcViseCK2yTLNxGtUUgo9Z7l5FlGnqk3oPeOj8SpxKnrahw4lZ0MTu3t71FVS2azA27d2mKxXFDXzQNx6h4LbDm8V4hfuco+0+RZRuPa1YCh1uRFEQrNKQVi6UaJ+hXcPPjoAttYXdW0XYXVMPC0EmD6tbP7PBQfY7exvARCX6o5b7O4VZfD38VwfR+X7tx1EeH9t34ERPjK038kkBPXn1uIq9rVDb96uuG9yyXT6fQ1N+NxgzGW3d09flpvYZ0hy3O0zmimDUwV5ajkqYtvoWlaZgdLqrZmuZzT+BprTej56J7DypIapsceejh1n8MWNE3D1StXWeTPkOc5WZyU1ZVgd86yu7fLzt4uO7s7/Mppw7bdxmhLfnXB8+88Ey15R1GEtmc6hIdOEh5XTnVQMWngTpy6du0qp06deaI49cKLH8c6w43PvxQ49cp1QFGOJm8Ip178/M/j1KlTPPdCWAxtyKmPPq3ZuXaNnd0drl67zvbWNsZY8rx4IE4dY2Kj760OURIHCTOUNXRrUedZfigNUSnVT3TyLkiVi+8lDg5657FNS+2DECsdrBxjTHC7Y9pjlgVC5XmBqxvC2qaRFMM+VcEhDyQK2xCFPpAhCH43wUpE+kWLbLjY1bEIxP/0p19le6KYTiZMp9O7S8+bHM45XnzrmO0P7bI322PZVDjrmE5GnDt7jktPXWS8WXL2LeepvKIxhq1bNzjY3+VgZiiKsk9lDPfarSxUuvGCbiIWdKaVzgryLDw4q8rx0d/6LS6+5Rznzp4lzzL29vfZ3d3jV840XL92g7puwgS8uQ7x3HLCdHOD8XjEeBSOOSpHjMYj8ixD65M19+Hx5VSoWqy7UjHhYlfHIsjYB8ZLLmzdemI4tThY8OFzmr3ZAcsPf+zRcOpjH+fixXPsXjxDnuXs7e2zs7fHtetXuf7/DTglD8+pe7BtNbGqV0qDSVdCzEaIVtTQ4vBRibqYQtiRoXO7VczDz+IKZZ2rn8VKps46alvTtqvaRnQTvxi6gj42Swhrl4bzZiqEA5wLxwptWs0uDrnfsXKqMLgxcVAUaJqWnz9/wFP6Fr97r2Vz81RfLfZxgnOetm3Za/YZlaM4mWqO956qbmhaQ5HneAQfZt7RmJbl8gBrazanY0wXOhk8kDpDynf/eY/1njzLyfOSshyTF0W/Dgii+BXvUWabbGc7ZLY0LQZDfb0GnzEdj8nynNFoTDkaU5Ylo/GY6WSK1ppMa8qyDGm1rOLRJwePJ6e8c4iSxKmIjlO/+UzO6Oqj5dTVq1tcv7FFlrHiVGtC4ck1c+quCkUgLhfqB98wuLpOCLuThPS2Ls+9d7cZNiAIaBA+1QuTx6MQVKbjgGHIfzc2FK8ry/JQnoIcPuJt2tSJcsicGc46hkBarbOY4x2sAO89WrFy8p1ld2cHpYRFljOdbvIYyj7WOprWsLQ1Gxub1E3DbH6wyurp1x+X/oFWLRc426DEkecaU5teTFbx9Phft85GlAnRGXkxYjwJ65DraDELwtatHZq2wrq2n/ClRJHpnNHGhFE5oixHjCehVlRe5GEt8yxU69WZpihCfL4rcniS8FhzSoXB48SpJ5dTx4oHeDgUpxsozR7GWHRekOUlTdPge+sLVh+C6yYETZkXOVmmo9cQ48ZlGXL0mwYH1E0TJmsV5WrJVAYDfvHVDWgqJSHNUgbhhe6m+BAm0DrUNypHRVgnIh7LeU9GIKYEo4rFckm+P2cxWkZX//ErYtg2LfWyxojlbc88S57lLBcVja0x1iCiqJu2t0bbpmZ36waFDoJsraM1Jk6QW61zDqt4bf/4FIXOCsrRiOnGRgjNKNUPPOosJ/OezOeMRiM2JlNGoxHlZMx4PA7jK3lGWeTkeR4t7U6+wlm6ORTDdUJOGh47TilNnhdkmUqc4snl1PECzH3c14MISiuUwNDQsg6s9fzrGz/Ml298U7+P+C4Txa/UabS6sixDRxdbhoONdAkl4XNYS9kSPcNo6QzTIT1KK5wNCw4JYUW6lUQhmnsAACAASURBVDYN5/SOfhsfM1byPCfPM6zNQmfFWDTRXc+yPMSIdcZhG+7xQZ6H2kFvPz3h9JkpXjzWQ93WbG3fIs9XizlV1ZzZ/g7TkaBF07SeRVX3DyPbTbwaPJi8i88/USjRGNOAwHgS1sB2cfavzhTPPvt0H4vP8pxRWZIXGWVZoPUgSwkQgpAbt7oz0lnH3t3uUk8O7oNTXQHIk8wpPzhL4tSKU192bcn83KknhlP3VCjdAGKHLtbaxUW72KiOMdu+bAC9b37I/OrKQoiEWKvSCiQOLsrhc4TkBomdanuNS9eGSDIGllN3vrhqNkrpmG7p+4N7N/g40MSdBdblfndufrcuxeOalKK0oigLTp8tQMLkuazIw8C8s3gfMoYW8wPq5RxMRZkr6rqlNRbn4/3obrlfDRivBqAzlA5W7Hg8YlSGAUfnHDbWJtKSUYzyGLfNyPOMIg8DvsHqkvgMHVpJPg5aBnEIy9R6utnb/gTetPvnlDnxnOqCMZA4BQNOnTnFPGbXPQmcumeWV/93IMuqH8WjV2M6VhoNFVAPa7KOIt6vjtnFfMPaEBon7pDPv1oLIpzAWosW1fOov6ZIRN+Vz+7O2VVO1Qrr7aHjriKRXVPCjOMuNC1xYDGQoKvGuur0xy3dUWuFkLGxOWG2P+sn0FXVEmcNgkIrOJjt01RzxDdkmWbWGprGxKOs+rX71P2jMk2Wl3FS1IiNjQ1G4xFKpLdgQ6ZRFtzzLCOPcdtcrxabEiGmO7poH6/gnY8lvuP5pbO4TlbI64E4ZdoTz6mo0xKnIjpObW5OVqVuePw5dc+Z8ocE6kjsdrBlmBAlit934U/gbBNcqIF11LtszvZk8ghK56AVYi1VVZH35QVCbFBp1WvmQeC2n8Ubuy2EDVS0zgj58J1b37WiW6zI98cP15fnBd57llUVSCQxDZPgV7Ztw4ffBmeWyz7m+LjB+ZCVYmNF0bqu2dvdYmOSc2pzjLcmKBtTURYZB4uKujHRmlpZN92s3nI0psgL8rJkNJqQFxk6yyiKkqIoQ9gjVq31Psz+btpQeTUIuwppsOJBHJo40Y5gPYvvxEtiyCisIKm1QonQNE2s1HuyBuUfhFPeB6/6RHOKlVI6Lqe251ucOXP6CeBU9sRw6pgeysCiohOcgSmF8K9v/BAiivde+OOHY7FCHCC0OGuxxnQeHBDicuFQ0Srqjij0xenwniwPTbU2lE/uXHUBmrYJMUUcWA+99l3l+zPU8p19F0kUiBRyrUVplNb89M4/4ved/6NYY2hbw/Vr16nGZch+eMyEP6Q4NuzuzNFZTtNULOb7bIxz8kzTNA2Xr1ymWlZxZT/LbL7EWI8oTaE1ZTGmKEItqDwvyOP6F1kWMka61QOLoqAoyr78iNZCXRucM4gQ1s3OQ6qijmmqnXiIEoh1qELM38VB4RDXb9o6lti2sTyJOnFrcNwPp5y1IdsL3hSc6ryNO3FKqVDCsuPUr50xPLOsHmtO7exu4Z699MRw6u5pwwMB79yhTqGtjKyYDtgJvwsDFMPYq/cr4Q+u1eqiDmcMrCy1oTsMq4ldzlpMjL82vsJDDAl0Flq0vFTP1cHROwtP+mvwseOcc5RlidJhINFaG8tQBHfcxVRLkQfLcewtgc4GeMQefpddMp/PMfGBshwJo9EYaxpsW8eBQ0dbGdqDBdaGNEbnwaPJyzDJqcgLxuMpZRnqThXliCzPQhFCrfusI4CiKCiLLpOEzhhCCWRZxqjIyTKF1uG1GoSMWUfdffYh/TW466v5RYEIDq00osPiUCcJ98Mp6yyrR/xJ51TftDtzylnKIn+yOLVcYNrmieHU3cvXxxnlq0qW0vnZ0bpauWTGGJT2fdy1UyxAvzypdcFykViqu5eAQ3HUuHpcF39FYraKom1MdNNB5RnLZhGOa13fFu8Ep3ywqiKs9SgRRHdU7cjlcES31Fqm0w0QYblYsLOzhb0YFj8qy5KzZ8+xOdmgKIpjC9gQq1ix78NuQ7zRZLDWUdcVP51t0boaRp5JPQrGgalRYkBCyKKqW5q4Frrz4LywuXmOyXRKUYwoijLUncqLmI5dxlz3MAgsMfRhjIlL2HazrHUvR0oJG+WI8bhARTHL8wxrTJhDIZ6qCtacdY62iYOXLsSLQ1mIkDc/Ho2ZTEaBPCdsDOW+OaVCSu7J51Tk1V04NZvt85YLF3pOfe4Nz+azjx+nXnjx43zqnRuBU89PKKvlE8Opu4e8nMWrsBocrGS/s3SIGQXzxYKmqWOpgLDucahGSliDobOe4vZKuhnAvnfLBYK1ogRxgheFGaRjddkrRVkwnU4pyhHz+QF1VeFcg/NDKyUeO1pXgo+ZCaEdXgLBrHV4Qr63MaHcdxda+PcufitN0zAaj/HAzt4uL3zWu9ncPMXzn9i/b2HzUctbaynLIsQ4reHWZ/wznnr5m1Zrhb9BsMayOFjy6s1PkRXCeFwyPp+xs32Dg9kBTdOwPw/rHxhjaVtDawzlaMLG5hkuPP0sRV6idYbONKOyDJkjsfChx2Ic8SHkwwJORRHSY+PsW53pUCAxy/DeobXC2ZamtTRtS2sNTdOGhxuDzCClybIRWR7jy0pTZGF2thBlRUHbVCyXC+D5N7Rv74b74VSWl5RFiWh94jmFxFTku3BK6ewQpz5ySfPu+TzMYSnuP+R1J04BQS4fEad+sTgguzF/Ijl1j+KQQfv7KETAIfc2rIUA//KV76MsR32Nl9dMfBkO9hxx98NIYbiILjbn+iG+I+mV/cWH0t9aqTjgFFeri5kjq4GlVemHrtnWWkzb4JylWi7ItIpunqNpmp4UYQArelvxmM9+bJuNzQaX5XR52d0koyxO/Lozwo/Xn/8JLn36feE6rePsx78Wnzu8X/XN62VZOedYLisW1YK2aagXS7JM9XHt2Wyfg4M58/mSg8WSRVWHh0KsShtKM0woyhFFOUKrrM/Wsc6B8ViRELWX1X0IVlWYLKW7WHqc0R3CpGHweH9/j3IyHSROeJRkqHy19nmX2qpF4gJUijzWrepMVKWEtm6ZzWZs3boBfOHr06EPgONyarmoKUfBSsw5+Zxq2wZnHYK7L05J5z11y9o+AKesNTRteO+s672vN5JTLz4/om0c9WZGtvPkcuruI5Z+5Yb718o+qwV0WkRllLG+T+8qdzvEN328VVYEONSYLMNYG853VPChz1/Hd4sNSZyYo8LgoV+lH3ZW1TCLwftwk01rUNZS1xVW6zCA6Bx1U/cTy7qFgzoCSBwA8x6MNeRZmM1qncUaG6rC3lNqw/mbpunpGAjt+hvb3fjXgwDWOvb397l+61pYyxzP+GyBcQZjLbt7e8xmC5ZVzbJqqNs2PiSELC/Y2DhNEev9KK3pH2TOh9Lpocdj/LarlCqgNZouXXRVn8p5h7dhhbnFfM61q9c485aL5EVYijbTOsSNtSLTKuTvM5DFLlYcF5Xq5EUkHPNgdsDNG7fW35EPg2NzqkGUphy9OThlW4NTFu/sG84pE7OiHiWnLl/ZCpzynvHoyeXU3RVKJ0B0Rz6UEU1XgiGU2g6uWmcDdQ3xA2tJlApejHQzM4WQFhln48rqHIcm2sRNu2J2Hg6lOMKq4qYMJKefANR565HIeaw4PCpHzPb34nmEZVWhRKN1xs/u/Rh/8Kk/Hq2vllYHN7JpG154bsIXXLc0TUvdNHzi+QlfuL2y426HkEnT0JqWV5/538i05ulXvhljLdef+wmQ4Ka/7cp/GDNo1i/9bdPygXLOr++8BDjOnTnFednEOktVN+zuz1gsalpjscahtGI6nTIeTzh77jyT6QRE4wkzqLWW/l76wQNPIThRiI9zDZzDOocY0G0bwzQWa03IUPJhFbuinGCdoGyw4vEOnYHzlsViwcF8H9O2eO+YTDcYT06R6WDFOteNPcRnr4SSE8VoY+39+FA4Nqcy8iIMaL9ZOKWzDLy7I6fCevXcllPz5ZILZ8/2nKqqJaPRiONxqsE1nkxn/WJkxhiQUGRzPB69/pz6hV+n59TpJ5dTd1UoOlYpDYXIhmJPjFeGiVNaa/79t/5p8iKnX6mtE8IYH3YxKyWkNKr+QN673o3rCqeFHuvcVenotzp3/EdiddWuvER30UIn6EAML4gEiyjTGZmEXO2yLKlyjY0xSe8cokNml43rN9s4N0PwvPDcBNEaUzf95XUW5VHUdcPBcsGLF3+Ez7z5JyjzgizLufSp93HlbT+OsYaqXnLrHf8MbQOxnn31mxG9PsHvLUkkCoWjrttAfuUpioy92QGz+YJl1VDVbdwnrGc9nU4YjSdonbFYLDC2ZTLZZDTZIJR8iP2/8sX7h5aztg9fdPITDOnorkdTSESFtMYilhkR1Yc8wLFc1rRNzf7OFt6bqHg140mw2LpV7Vz38JSwrrrzgKjwkDtBuB9OjcfjPhZ+0jmls1gHSvydOWUtTqlDnJovK0QrjFktLtZPlDyCjlO7s33OnTrdcyrPDHXTYKzB1Rbf1TDLAsdDFlni1BvBqXukDYd1pKN5c4fejdkAeYi7dqUBBgdZdYj3h8pBIEP7zB86xcqCixseIUA//ni4QXgfYrL9zOOu7RIEoEtT7Ky74Ia7LuyMVhIHSn209EIOdqsMVd2Q5UXIYmlaZgdzmqbFtBneH06lq5qa2XzOze0dLh0ccGbzFONYGmGxmNM0DdnONvbtJoYYVoKzGgR9cBgTBuEWdc1kVPbrSisllEUBPoQVZgcLqrrFWE+el4P4bsicKcsSpTLm8wWig5BppfCqf8qEFQEdvevcP8To0lvjzezjsarPoQ9WdSgVopTgkIE1HMIwbWuoqhpRjlgpIiZWdBaz72UxCIfvZeeklUY/Nqcy/ebilDpcUuV2nHJ35FQeOdX0nOpkcIgVp7bJlH4Np9q2BTybG6eD4k6cesM5de/y9eEScP7wL/36DSJkWR4K0nkfLSbfbyMiwWXur9+HmfydFeK7C+isKjW4qBWGpOqE1ln6wa0uVCASitjlRY5IcK+7mb1dvntHROdCro0LP8aCdQrnhfde+GNhWVZDvC7HYlkzVoHk+7MZvzCZ02Yt55cl3h9Offz0Mz/G9XKbrZv7fPz8D/MFB3+aUVlw4x0/yZWPXeXg4IBP6r/J5/vP48InvpEsy6ioGI/HHM7Ll0OxzEN34S78WFQ1W7t7/OJ5y5duL7hw5jRKhXkmmxtTFos5+7M5e7MlZTliOtng1KnTnP/wz7CslrRNw8bmhL0LX02WFezPFiid9SESHePhzrso4C4u+EO0dFcPmzCBzkcr1aBiKmLIZ/chVdEa6rYhK8aDjKVw9SIanZU4V+G8R8UiddZajLKrAohRZjr5WUnxycFxOaXfjJxyQYPciVPG81pOVRXj6BHtz2Z8+pVP07Qt589deI1CmS+X7M5mbO3tU2ahyOGoLLDO8RuTv8/BwQEex3v9d/XyU1Xr59SrN2/wtqcuHptTN2/dYLkMnGqaijy/8Nhy6u4KRSnE+1X393fAHxFOF92p1WSYcFoFyvVWQp9nf6g9g8wOa1BZsSKEs/0Fwcra6CZZOe8GufXdVkFwsjzeKNMemkAVQgUr49D3zn9w+4rRGGM9NtbTCcu0KqbTCVkWUhutMSyWC3abXYwxnD51mqPi2eXxZ0qxt7/PJy/9KBfOnGExXzCbHbCoK3RRsLW7B2/9MabjKf88/xa0VhwsFnxFFVbd++03YDoaA2GyWShnfXjhpdvhY8+OuDpacmvrFr9wdsLvmS84M56glOMtF95CVW2yrGqefqbAxiebzjRnTp8hy4qYGgh5UZDnoayDF4V1wVJzplp5eqLQKuu6HqU1B/v7tG2NcS2nTp1jMZ/R1EsyDZON0xTlmKIYAxLTGA2e21ybhAwTnWdon/cVdb0LpPE+5NSH9W3i8qQxzvy6jMI+JI7PKf+m4lQfVpO7c6psf4DchUly03LC7md9EYsi59wLX8srb//H7Hzoc7HGcOa2nAoD/bvv/j9Yak198SkunDnDfL5g9tEVp7Z3dzl3VpiqwFljWnZnQRllWcbFc+ceiFP7szlbezM+9MyIV08Z3vW2ceDUR6/flVNte5YsK1ku5iCPN6fuXcurfx+zRA4JMnhZfb/KAolpgWFpt16Y6eJ/nl7keq3nY2qhPpyLEuKEcujcnTYI62hHLe5X7eziil1scXgsOleR1+rZ1X6e92/9KF8z+bawTRwkmx3MkKXC2pabbwF9+X9GeTB7F/it597Os5f/SD/gb/I2TCAyhrptWS6WVOMx0+k0WCLO0bYt88WC05ub8SZrvv3Fhps7B/ziOUeWa5bNiLIosMbya+O/S1nkbEw3OHP6NBde+ga6WO5RWOt6N3tR1ezsNtiqwm40nD1zitZOmS8qRGfs7s6o6wZPIECeZ7Q2R2vCzFxRfey+g9ZZv4CPBxaLA7y3CEI5GmNsS2taWtvQtE3oC2sxLshBJ1+Dng/FAweDv6Hfo3UUF4jKMo/vaxCt7rkDcCH9OqwfMZTJk4Njc8q/uTgVHjZ351TZ/gDkBV1mmhCKI4rW3Dr3g7itipvP/ZPQRxcucH7rP2M0GvWcuv72f8LWqV3c9t059amnf4z2qac4feoUz7zyzYCwrBpu7e6jc83mxkbPqVeuXKYocjamU86cPtNfyO3k5pV3n+XaNvjtLRZVzfbuXuCUvTunQkXgjLbI0dnjzam7K5T+n0iEaIr0gk9Ym6GPubFa/zgQA7Cud+UHdlG/bSes3X6vGeD2h6W0HxikW5vB9VVQo4F0OA4Ifcx5aJkdknzfhSFu82N86/Ds7e/hJazRbeslyoVrmy/mXL9xneLWjZBXXpYssyVtU+PaFmMti8WcxXjEqc3TKB1ms5q2Zj6fU9UVG3Yay34LjTHszysk1yxrxaRsaZuWV3euMCpLLpw/y2Q8CetAx+qyR0nQu6jWslwadvdqzDLHjBST6YU+ni06Z293TtsavOjQB4qQPhpXfWMgkN2DLax2qeN9sCzmB3hv4hKwKqR+xrUzTNsGa9t3ayockchuPAvN4LHYh3E6690YE1x151itzRCs627cywt4QkkR/NBWPhk4Pqe6Qfs3B6de08935JTQVa91EDklkVOLMFgfOXVj93q/iuADcyqmDDfGsDdfIJlmWTc9p165cpnxqOT8uXNMx5NQDPO4nNrdxZY5xjT35lQMVT3unLr3eihxIG5oQcVT9gTosw5i6poQ1712oR5RNxDn45R+Hw7YC2dnYfVmy23a28cSGZSR6GRbK5TTqzYS8tqVV4EcvluPoev2uKMSrF+Vlh6q6Pee/2OHzw/cunUzZEyIYlT9fTJACywODpjt7/Fp+V6U0ailxu8EMjsfMsW2t7apq4qmDTV+vGlpq4ory1cxTc1iPudPyQLRee/21sawPZsFN/8dP8Xs12fM2GNxMAPn2T7z/YzKEZPphGc+/YcZCpVWCt82zG9ex5iaj1+8wJnNDFsv2J/NWCwbbm3v89zzz6HznCwv0JmEVMKDGctqwZmzZzpDJ1h/TYMtzaFe8R6c9VSLitEoLNqjkDhAqNEuTAINOfY5mc77WP9rHnR0D9R4n+NAYOBpGFi0zmPakC6qdIlzgohbWcIKtNVYY3HeobKTVcsLHlNOdZpSKbLmHyJxjKVUJWW+gbaOim5DoXvI3bp1q+eU2OYQp35Z/Q1UrR6KU+W7foKnXn4fIortz/jn1Fjyixe5NZ2iHbx89dcAxzQbw+X/lOlkg1E5YjqdUOQFd+PUxFwg35xiTXVXTi0XuytOnXu8OXV3haKkKxHTo0vr61xm6CyXI0Z/98xWKsqaRMH3QRMONPSwtpEfFCUTEbKiq30Uhvp6CoigdEaWdTX7VX/ioCBCB6s487fbRnUphA689Zg2pOKpLrUuEujf3voRvvbt304/JBWtj3D8WMLZh/nHZGFfS7DulAoWVPAwo/VlWqrlgv39fepqibW2b8tBVBofuPQ/kkvB4kyLbr6FzFlePP2DjPOc6e4I01SYtqWtlgie06fP9nWQrkz/Jgv9rVjn0Fqzc3WP+Wyfca7xeoxYQ1Mt8M7Egm8+1hBaCaD3IXfdtG2wgOKEOIn3SesM4sDhUeRlSVFm5EWB1hluGcqWiwh5XtLWLU3dYpSlGI3JovsNMZyC9CZtMKCHdm+wmNqmBRxGa/KioCgdohw4WcmmAyc+XKf3Jy7L69icgjcZp6LHdRdOrbyoWP6lk4HIKV4HTgG8nP+1wKm5JXOWnVu3qPb2mI4Oc+qDTy34nGsz8rwAgelkgnUe6xzXP/fig3PKdJxqcNY81py6R9owA+tm5d6GHwffM9CMnYU1IIaIrFLgh/3WadTeYeg2GrZhQAwfqmO2pgk0cO7o5pGYQ2c7uIu96yrdqX1vlXVtdt7H6q2HNX3v6oqHuKoDrlua1YPp7LzQ+84R3F3CwJZ1DmugwbNcLmM3rOLXdVWHWbHWUBQFojJcWSNAVR/QimCqMsxINgZjPPv7+yil0VmOaVv29nOW2TU8Ql7kHOzt01Q1udaoTMJzzFkU0pfLts724yzeBwu4LEc0TU3d1L3grKzR7j4MOib2uYpVULXS/QPHe/CZ75d6DRb2a9NBD9/D4WNUVp+7++YHYYLOova+/00EvHRjAHd2zR8Vjs2pYajqTcCpvtlyJ04NlcpK/rtzCSvF93pxCpUheKp5fVtOmf199vddGAM1hv18Dwc4hJtb+uE4VVeRU7rv98eRU/csX9+FiFYGxmpgpjtvNzgI6lDDILh1OsuC0HUSOGiTcytrpavE2gemBo0Pab7BRTTW0KUrhxmiYVW7bq5wbHzfmV18dejWr9oe3oQ8eUfThqJ4X3X+j60aGs+N0itLMl5zqPpqeotPRPAu5Nl3hBFW6wz0bYv95uJ1usWCGzevUxQFGxubnD71tymznLqpcNZwAH2xPe89y8USrXOU0jR1TVUtkex/QOc5avM7WOztoiSkNJZFhtbhnmmtaVtDXTfUdYuJKaneh+q1Nz/nK9nZ3eHCR36GTz73RVwkrADXl+g4cl+OyopIsGBH5QRXxBRYnYW4tHTLvq7uTexeukfm4IiD30CJRukcwaEz1cfGhw/PIKfSy9NQDk8Kjs0p3lyc6ppQNP/wjpzqik12JvNRTrnXnVNnyO7CqWax5LeePRXK+NeOqlogWYbOC8ZbOw/MqfPnLqCUprWOsgxZWI8rp+5vGrFaKRDnhk31vSaT7tzdoJ6EdRBCqW0XB6VWJs1KGUGm1CAaIDgfJkWFWa9ZrILqwAplWcaSAaEtelijPxKoa6uwEjytBesMmBCLHo/HYe0HF1aSq+omDFLpnFjwAOdDqeh8JKAcRfMPMW0Ts/vDHVI6WCwAxrneq+lSP4nk62ZCd73XtrbPO/cWmrplIYvgAUXrDgirsEH/MnVD227TZ214j8SBtQ2t0JunqJuG/YMDTm+OKdDBt1IqVACwlrZp43oIoc9EhPMXLyBauPyuL+HC2TOMRiNMGwpqtnZBkWeoyWY0XVZmlQdaY5G6oZCccjxG4j1pm1BdtakbnK+ZbGyQO9vtGojX9QGvMZCj7EUb1Luw8JMfhE36R3T4V+I9wcuAaCcUd+KU503DqYn7QbJqgs4yrFL34FSnPNyAUzG89Yg5xcHfY6f99ttwylNMJw/NqbpecuYx59Q9i0MedaePutSvOfRAU3aKzBgbU2gtWd4NOgeZP5RFES2yQ+cfHtaDSJjUMxqNqGOneudwuL5wmsTZxd1NETr3PLQ77BNu1s2XP8SF578Aa01vsWmt+ent/4WvmX57vzCQaVtUloeBsFg2orcCnENUWNNAfLe6XrgNvs+pHF6W78t6d/WTPL73Rk1rWEqFNaFwmx7O6I/74zzWH54BnGlNFufNLOqGuqnpSlh32x2VBR+vOZTrCGQzJkzAMtbEfUKc25pQI8nYllzGqwCISKgfZB3eK/Jy8hoh7isT+JXF3T0EwgC07+da9AbKkf27+6+UZjhRrRvM7j8PvPswcHmC8BhxamR+IB5ARe8BnNborMDDazglMfU0cMod5hScDE5Fz6i7E4lT8fMxOXUPhTL42ymuKFBHXc3ef+8uqm+M9BV+u8lQOltV1RyeylqH0kPNSGe+9dt1k3CKcoRxoTJpcMUIs4ejG+kHFlS8dxAjwc5Y0KHODX21zrBugHcer4JpaFwglrWGpm4oyjYMfHWWQNTuzjtU8O9Dip3zfRkDYl8dInm84d3CNn1PyaBIX+1pTVjCM8sy8ljHpxeMeFGdOyoSZtpmsW+7PPUsrtLW1cbriNeHTzx9UTktIZPHGENrGowxkZQCcbZ0WMehZdzf3Xj7rcf4loHJzSqdsRskVr2l3RG+I0I/eW9gHXXHJ+4b1riAPMsOxaJ9dyGxb8UL1rThZVtOFI7Nqe7Hk8upri0eYgJHeOBrnd2WU0LHKf8aTvUzsx8xp8KEUIn7hkl9iVPH59S9Q159Jw0GbWLtoG6grY+l2q5YXSx5Ld0D3PWrwnVrTXfH7IniPU4cxMwQgbhGwyrWG7RjXNM45nILwXq6+sIvc+ldX4x3HlWEzJOQIhdduniOroaqEkWmFAezGaebBiU+Kg8XiWCYz4YLaQnVfE6eZ+RURPbQLcUaVrALtXoEH2+w6wVLxVhxr9h8jAH3ykl6K8AhSOwnj8cSssrC5KKu34JQdu9HoxGy8WeQ0ZjFYk6RKSblmMkkrNYmUfCruoJWqJs2CrSlrhYs5jOyIgiUznKKcoKPIZLwTFEUWYl3UFd1L59de0JMXa9CNJ34EPqki9Uv5nsUowl5Oeo2CKQQoa4qtNahKm1cWwcJs3qLImN68SmyLFiW1locHhczT5w1uMGA6MH+HsvFnMViBvyhe4r5G4pjcCpkcj1aTjkXy6HfhlNF8/2HOKVUVExKczCbobUMOGUHnFoMVA1UZAAAIABJREFUOmLAqb6UyKPlVDcGVGffymgUy7sUZeLUMTl1jwW2XEw3G1o+wWrqbgx+JXRIdLMGcbu+AibSP8x7TU4c0OsExTtylQUiuFhhtdPk/rAL1lt4wPWXfjkq4VAcrTtHHxN0qwJ7OtYW0jqkW7Z1hbcGleuQXy1hVmiXkNlVX+08AK00WsKMVmMM3oZGKIm5/NG6c10/xFIWzpgwkBg7xnlAaeIIIl2pjGF80vmwboKLM4DDYkmrsEewB8P21nnEOry3TMYF2bQgzKLuBgjDLOiDeY1kmtZYwDGbHfDCr/5b5vM57/qi9+K9J89zNqabjMtJGPQrMi498zQQ4tOxkCz9DYnEWi6WgOH02XN0P3QykOcF5WiM95tsbJ5iNBp3YXnwDmdaqsUCcGR5HpZCcI7WtBjThli/NyEU0z+kZBWSNOG3rh+tMXEiWPdwORk4Pqf8I+VUjwGnwsM2WvRxoNx7ek4pFbyYtq5QZf4aTnE3TumTxanAl7gC5QNwan9/xny+YFNvPFGcuscSwNFioBvuWrl0RyWvE+i+DlC0oFdWlQy6o793dEcPVtrhBP1OGLrjeVauHYOX9x7VlX7uSzV3BfVCie3eVUf6m2XjqnJh21VZiRBb7lz7aLFJqGujtBrMI+gszBDn9LHNPuauEz23OPSFc0EARenwrYRV0ZxtGbqZXWy262fvw/GUc4N+idt0DyDrgtWRa4pMIeJx1tO2QUhUXBb09OkxrdNIXdMaQ1u3VHUdFv2KLr/WmtFoFEunh/aPRqNItCWmDlVdh/MUsjwny3Ks9Rhr0M6iolVp2haw6EzIiwJrDVUVlo32PvweMtXmGNf0xfKcNRhr+lU2jQ0DvS5mz3QemvOBDOF+hdIWrq/OerJwfE75R84puS2nYk0x1Q+f9+f33vfr3DunXssp7sSpw8r1JHAqZJo9OKfqunkiOXVPD4VOAOON9ANrqrsRnQC66K2sBJND1gFwSLi8Z1W36JCVMNhHosLt3OvO0uprGHkuvvN3cOvlD6Gy4AI70/SF5ERCrlZHwnBdocNe+dgHoosaOk/3g4Nhprz3XawwXEuIMwo4F9YmiARbCabgveAGcdwgeGF2cXeTlGSI0rzy6d+OiOLpSx/AexMFKoxJdf3S9bGP1mXXTxKtXB+vR1lDnimm/z97bx5sWZad9f32cIZ775tyqMqaq7qq1a2mkUBCYdTCEsjqlpEghAGNKMTksAMwSCEkYYcJRxj9RYQRGDAKR1gCywIFttS2AbeGbkmojdFMhBGopequWTVkVQ5vvPeec/bkP9be55yXmZVVXV3qrgCf6Ox6+fK9c8/Ze397r/Wttb61aEAF+n7AOc8wBKq6wpia5WLFffc/wOHRGYdHR9Lb2gmX7ZzLQAwYrWgXDVrldwFJP03SFnbo+xkAZV7aZYNSO/hhoO8HtN6ilCYET7/dZEXUiK00JyeH4yIOMWfGRC8ray38uvOOUKgeZFPyMfdO1+pcymiJJ2kjnPBqucR5l42Fd9ap8mYxpTLt8bnClHjzhp+IW1QUTPn4xyB7ON/Ah4VW0ROmSJEwHoKBENQ5TJXlnd9yhikpsHw7MCVxAc0Q42eEKdP9T3jz5z4DTPX44d8/TL1xC+BzbkhZB5JDncI0OaXN6JhVkBf53OJPxcJKk41xW7Bo/CBGS4RbAJRu/V4+UV/6zV/IAT/HlSe+WE5WJaJxZI2elCS/HqVJIUpxoDHo0YsRn/Gf3/hhfv+Fbx4/Rn7PozUY35OyV1By/ucLNZbsiny76d75Z6L0flifntAulqQkmSfEbH2Vwy8l6QWeFCoXORWPatwVEGtxZ9VQV4oYHYNzdJ3H2ppLl+/hyr33sliuqOsarRWHR6dUdcWFg4ucna1RSjJybt64PmqzOS+Ngaq6YrFccvnyvaAU3js2mzNeufqCcOoxMgw9Q7/NQcsg4543khCiZKqohNJQVzXbbSfeYQ4wxiiW4KJtadslMVZYX2GMxBFU3vhsVUHmjo9OjvM4lMWjxjnpuo7Budus83fE9aYxxecEUx/xZwxuwA0DOlXybCkRvIMkVdraKD6cvh6lDFoZ/nj6UXyQ4HFCZ4VaexumynvdCVOladdniinnhrcNUxfrf0Rdfcf/j6lPA1NvWNjIbFJHdzSmyU3O10u/+YsAXHni9+T0wBEr40IuPz6XJph3mivWTn5XzuMuze5TLLUpQ2u0zkjc98SXUFILi4urRi9KFqbKzWxS9jaizq54Xu1/4PK3Ef0wAra4zyFGvPeZeyWDuQBGlW+hlSbmrBiZ6OIJRYyS+lvGMSVTIcUim/G+BdAxjhIWE9WQO6wZg1r9OdH/6T3L1S67uw113bBYLFnt7FJVFUprQm4SFIPEk/quk/cPkWd/7f/marukqioeeN+XSQpmjBl0gRTCSBMe3ryW+zcIcEjCSYcYJciqbLb4dK4hkPc0StM2zcyClqrmMHLag1hPWo0jWigIAeQsFpDHomyj5HHq46S0PF9D74Tr08GU91njKaXPCqY+4k5HPH3PCz8MRo/rLwbP33jkT8rPx0TSZExFQgr5kJMNLoZINCE7M7PivUw13wlTKYW3BVNFVPPtwFRbV28ZUwUnm/UG4jWJYVT1v/OYenOFjanMQpkMzi38lJCGO0rlgqj8yOk8QEZrIkGWvcx+przmmAY9rv7Z7xU9/vxvsVhm88Yx57z6ydrIkMmByjQblLyo8/sIryuPNXLQ+YVHEOdAnTZpeh7mn5tBpEHHSXyyuIrnxmPm3k7/mb5W+TnESg3EaBh3lfy7WmuaWrJRJCtEs1rtsbOSBW+spapquVc+DIu4n1aKYehzllBk6L30rFhKYVrwEVJF8HnR+2kxrden0gBKyZgYY4SbjRFrzci7ai1CdzH3h0kpUtlqfP4UI9FH8F7G1ge0MZNEuuxC4xqTDJ84jtO45eSxSzHhQ8wN5tL5ZfROut4QU4mQuXoUnyVMld8RCiRDZLrUud8eN5wiUomZKKPynG8aU/HtwdR0aLwdmGpxxr4lTMUSn+09p87TLhe0Sv07j6m7Higlmj9/jvOTNf338mNfnIuXci5zTEAkFCtLjY85usEpJX7uxj/i91/8E8BUFTst1szNIpkxcibIhu7cwNVP/SohBC498oVoZZi46JRP8ulSjB6vLKw8eFXdiPiaVpO7l+Dnrv0wX7H/TdNCi7JYYh6MvhtGt9s5xyJLIZQbFFpB5d8lyW2kIEqhjEZVZnqwWygIZhOX8jimLKOhs8y9UqLbtbz3L3Ph4iXquqauG/b292WzSNIMrNuuRwu3HzxN26K0Fp43V0YDY4+G6AOu3zIMgUV7QbpJbjusrbCVZbFYoE8lU0eeLko/73yfYRhQID9vLSol/CBxmr7rsNaOwV6UZKvU9WI83IlkRV6d90eFteSis4AyUWiEKIqoWoPLMbPJ7pZ5foeFUN40pkCoDWPMWEj2ZjGlSnrvG2DqvU//D/R9j9KKylZ8wXJJDLniW2sU2fNHimi/+/kfGuMM3/euPz1u9KVVbekSW9cNldW3YUql2YP8NmEqn2qfMaYuXDhgeeV73jKmYtmDslhl+PcEU29cKU8ZlPwtVSZ1cmWthtee/mW0sTx5+Sn+o3u+jeJWguS5V7UlmbxhpUTygZee/GX8/YMUZymVU9sMikBQGl9S2tBoLS6ZtTVt07K3e8Dm4IDgAx9vFd/7ga/NgaXAMPT8vz7QdVu67TZPbK4qVSlr38jEuaHHDQPJ6rGSl5T4A5e+jeD7c/SC856UIiq7yjGIZEFMEmydFrymnPY2C7qVdLsYIpWpsbsLVo9cIVw7lZ+8AzdZehLosmkwEgCUNq1aaXZ2drh48eJYGeucg1SyRSLXrx2L9o+1RDSbzYZhcDg3sFguR242xpT5bIUxFfv7e+wdXGCxXFLXLVprnJbNLDhPGM57WypvYClG+m1PqiJ2ofmSymIXFzGVpV0sIUlL2AgZeHr0sSfrtvy3WGE5iFpolhnXrojCcW/XDMOGT6DOUUDvqOtNYsoo2VaYUbpvBlP/pDumWSz4ruf+AUop6sqKpetDFkwchPrQekz9tWbCFIhFu91uuXTpXqGwYmToO87OTgVT3Ta/AzmmYkavBhLD0EPSpFl1fPEC5hGkOabi24Spam8pmHJ8RpiqLnz7Z4Qpe3I8MR8ZG28npg729rl08RLW2hwz0iQUoXzmTBE4Zg80jR5GHOckFdovU1pTz5PI4B3dZs3QbRi6zZvC1BtSXhOlpM5JGhQJbYVUuWrSZDAJ4ZkNBOF/DbKAldJSZKMMe3sXuHTxHvb2LxJjlJx0Y0gxUTce793Y7MYaQ78aqKuWdrFksVqx2j1Ao3jo4Ud5YOciQ9+z2a5JMdDaGpCgXwy+zM8MuJN7XGIrJkm/gKKsOloz5za0vKkVXaVxQaZzX49+rCrNesLoHaUkCqEqluK0CWS3XeNNlQBy9szln6Xa1RLJGTLeo7VYLOQqaNAEHzk+OyVECXKKC53nN5UCt4qqqrPlJNpLwUe62AMi0CdjaFBq8gjH8c2vnpKotu7t7fPIhYtyiGtJcSQZ1tue41PpSFfWldxLTeOdx1oAMRMCzPNVPlWhUdpibIOxEWIgecfUMOiddb0pTKk8R/DpYaoxrHZW7B1emGFK6g8EUz5jSmGNpR8G6qqhXSxZrlZAQqO4fFlzcOFAMLXZkIKnbVsKpgobP08BnjBV4pURk8y/l5gq3pHWWtJ/67cXUw8/8LAYyFq8kYRhsxFM+TmmUiKiJsyMmXxMmMqua5G3uQ1TVYBheFOYeoOgvNRdlDoO79xoQWpjZCJSkqrR7JIWqkkXLnCcO4020ub2i2xFu1ix+MAf5sLBDuv1lk3XE6IfM660MmPGgihtVviQ0KbGVg0hefT7vpzlouXPP3CFxiRuXL+Of23gb6Se76LCac2Jgl8rPVDG9xIrpBxg84OlFDXNA6aKGQAobl8SSkBwLqAq67VMWLYq9ShdIRAJIZA2Pb8WfpmvfnCLHyLjjcsD3rL69ViaO33GHHYxhNH2iz5gaoM2CmMtFy5exjnP2dmGV199lb2DAypbYWxFyjQJCh76/A/QLpfUVSMBR0V24T0xgI89VVVjtPRo0Pk5YvCgJBg71ikoxXK54g9cOOALvvAL6Puevu+JyaNVzStXr/HSS1fpYp/7RJSNdZZOO6lMyLuNw6POGQdaKZQxYCpsozA+EPzJOGfvpOtNY4pAIo54uhOmPhI2qCSY+m9f/ce07Q4fXO5yQe+wfuBRNjk4PGIqixiisnptXQumbJUxFdApsVw0PHD/FRoLN65fw3tpPds2LcYYQkh89/P/C3/r8T8DJP53vgGt5ED74/rDWGMmSu+zjCk9BFIuyPt0MdXZP5O9ut23B1OAraq3HVMPPvDgeUxFj9Y1L79yjRdfukqfevwwjM+fUumZcz7+MR4mhcFJTJjSkgUnmFphhjeHqTeuQ1EKlUTIbei6PDmzeQE2faAPYLTEN/quJ6UwTpzKjamMNdx//yMcVA22blG24myIOKXBWvDSqjNG4fXDLPMAygkrJ6kbenZ2L3BwcJHV3gXuubDggYcf5pHHHuXHjo64+spVTk5O2Fnt8vTxCcPQCV+oJ/f5nsd/N6k09cmVyDFJ8mOpAyAVm1EkLorUuJz4wg/rbJWpUvE4m7iyjhWILhKJ4AdSDMRB4003WmbzqwRj0zjJZqIMZpNavtZWROwUCaUt280xm41j8IkHH3iQvnOs1ydcffUqpm4wuh/rTx55/1fQdVtCksrh0qa0265p25amaQhB0ZqFZNrEQNF2QoExVa750SMtJaC7yBPvfgLvA5tNh/eOCxf2ODo5w3k3Ul3aWjkQ8mIu7vc886mkjco8SbUzOmsqWaF1EiJc9ztTz79pV/h+i/f93Zb4Z/16s5gaUgKlsCphdCQ4dxumOrfBWsv99z3CAVcypixnQ8ChwIo1PHhPTGJdluAx4xqOM0wN7OwecHDhIqu9i9xzoR0xdXx4zNWrr3ByfMrOcpdXXr3KX3nxRwjB8zff9adHzyRGT900nzNMESPeDW8NU6pgis8YU02zJCX124Kpd7/7Cbz3bNaCqQ/c/CGOjtcsX71O/cIrbMN2zMj6zc/79izsGTOdOO0fMSaR8MlzpXKMxdhbMBUNbdwjpfCGmLp7pfzc7cqmYiLlSvHJQj73O0yb3HSfiNEGaxvelyI3b17Hh5gnt2RbxLEwZ3RX7+S2ppKd4KmrlmEY2HYDkaV0m6sNy9WKi5cusFotCfdGLh2fcPXVV7h+/Rq/FiYxuOB95lknd1olxgQA8sIqC06UMG7JclCgtObdh1+G1QKTT+z+y5G+VUqaAcWiDzEfszS7BzBWPpeNVYn3V3oelNRHpSWtsow1SAc3qyOkgKkqgq/p+oHT42OuV4azsw1HRydYa7BW6geMiTS7NT7LbfdDpO97gpcUTufd6LIrrei9IwXh4acEh1ssluw9fKGGdxmRRL9+7QbXr19nvTnDvmSom5bNRu4xdD1Fa00pha2rkf4oUuPplmyerA8w5sSr3HPb2Nx0KETe128ZgucT+tPr0PDbfaWU03O1nizgBH/I7gCJ/8ufAfCH7e6535mP80f8Kd/1/A/xPdpQ1y0P8Bg312upW1FSmR3HQ/mWuo7J0St3l/+PYuXXVcPQZ0yljKnKslwtuXjxIqvVShJh7rnE1atXuX7jGt/5zN+nqhtA8dTDTcbUTKDxHKbSnTE1f6SMKaNVxlTEp/TmMDW/B2+MqeKVoBCtL965mFouV6xWOzRNw+Vf+F64fp31+ox/3WRMrfvsAQ25YBPe/Ym/KZiKiU88/hdEq2uOqTjDVIKkIgRybEzoUowi+khVt6QY37r0CmW6VFbWzINdtIXKv5MD3kI/yGIoKboo0dEytqKuW1CW09MTun47La5zO/Rsxc+ClGVQx5/K8gPeOfrBEaIsWpUna7WzI5kTxrC3v0dKIqTG0XH+COFcSxbDRFZP752fhpIRNgdCdoRR6FmTG6l3kQAjSO+ANFoL81d83SvNeeP8JJmfTmSJGS0WzTjGSCtRo0VLCJAOdQnc0HN0dJP1est6s5UMkczha61p2oa67kUqwqncz0FSCWMKwtUbS8z0jHM93vXnqAKKQvqMilqtVrRtS4xw4/pNXnvtNY5Pj/AxcO+Ve0lRaBHvRI22uN3amvEgB7HoCwDIfH0xRFJKRMTKragyrWOIVcDWkpdf3WWoP2dXiePpHBpOWewvlUVMHg+JO2mtiHNMZQrJmIwpbQRT3ZZycEzcOJxfcGrcQOXr6UfSOMcZU5mCVEZj64yp5QJtNHv7+4IpN7BZr/MtkmAqhXOfd+tXd8LU9JQzTKlc25L4NDB1B3B92piSPeGdiKnFoiXGlDH1Ksenx4Kpe++lCEn6YZiML1V6z6fbMZWlVkbKvxzyURIeqnQHTI175p2vNz5QtMZUhkrXKGOyBkwguTAy+FoZHnrfB6gqy/PHz7JYtvT9MGrBQOJ3Gc1u03K6WZNQWFuPKcbzVZ2yFVPm/fWumCTDox8GhsHT9QOLZU1rNBiDNjZbGxGt4cp999K0Nb/0b38DzhQasYb90FPkqlEqB+fh5w7/IV+x/40j8E0C0iS97UPM0tbiMXzq4Bephm8hxoSP/2KsbhaxNaFpyjWnrcRCnbmhQX4uZguhjE3xTkwlQXN3JtRgCCG3Ro0kpYnRcHqyzhZKxWq5YtttpF8FCqs1fd+hlMb7RO1tzpgKOfAogWHnfF7fEzWxWW8YhuzyWkTqArK6dpwOf+DSpYu0Tcu1167z0ssvc/P4Bl2/QeucLmkajNbjZ+oSO4lp9DgAPOc95dKlLqR0i/su46aNoVm0xBCxVc3veQcG5rVW2ErkwpU2hBgwqRFMmUreU1lsLSq81hqqyo6Y+u7nfpikNavVLrt7B5yuNzK3VZ2ze9Q57Ez0z8wlPvd3uWKKhCQdFofB03WOxbKh1VqUJqwlefEMtSqYarhxeEgiooF/Wn8rXzf88HjwoRgxVejmO2EqpnAbpnzU+AgxaXxmMeCtY+rH9DeN2WhaaepUo/wZdd3yn7QX39GY+og74z37NZ/Ujt/383+NX3/pJW4e3xRMGUPXbWeYCjkOXWJXQp39jme+H0AKL70cnkopPvmeb0drRZjhaXQaFGibMRUFU4udyXu+9XqDA6XkUquc/pdTzJSiObiHSmtUCjTbPapmkYNcRhZQVh8tJ2CzWFItWm68+ppobhmpG1HZAiqLJDhPSc4fD+xZvGAOBOkzMIji59mWtq1p21qKeKy46oum5uaNQ/b391kulzx4eEp1UtP3Hf+kPyJ6n9e9LPYP7u2gdSIdSu69jgmjEtaI5exLzCKDI0aFc56YFGEYSAmiLRYU2ZoulE3m/rMjbrRY3AIMGbNLl+6hqWuMrQhBUqCdc9LzO8S8WCYqY3COs7Mzrr32mizcGNn2DhJsNlsOD2/QD1I1G0LEx8h6vUErA2j6q1fxu7tYa9ldbzhetNkjlR4bfdchbWjF0jHWkghEfA4Sa0ATQi/8qzZUpqZtFoQQuXHzpuiEZcozRRicQys5GBVK1J+1tJQtBXWFChJaV7zcYs2Tg4bFCC/Bxvn2WLfSfdB176wYSnmpc5iKkX8Wz6hWF9nRS1SK/PSwReuAThEd4Due/oExcYFK2vQ2yyVVu+DGq69K6q7RI3U4YioWTCUkBXmOo/lhI5f34vWLiu6WdlHRthXaWokpWMOirbl544j9vQMJEj/4IK++9ip93/Edz/xAzqqUd3zusZ3Rwk4kQor8n+mbMUnzjebDE6binTGVz4ZZDI27Y0opflR9ExGJN2mjObh8iaauecRUhBgY+h7nJcU3+kAwUthX4gyfKaZunp0QlAhHKsTaf6uY+vynvx+jDb/b1Lx3/3Haw5Ybg2fwIt9vq4YUE8Pg0U2dA/9q7Nki60GPKgWkUmxaMlrh85/6u1kpWqjElBMWmkXLs1/wPePaqNsGP9wdU3c9UKThijpPTaWSzZW5/FiCceKuh5DdqRTLaUBTL7OLB84N4oIpxkVUXNJznF7OaGHm2pbsEPlLFlnLIOsHz+A8PnOVYxqjloyaqq6p65orV66wfG4p8ZOiqKnIAmnC55b3DT6QTCIlnZ81W8BNC0pLpkYs8ZiILi6ktrmTZ4kTlTGUcSseUcmAqWrJnjHGcOHSJeqmxRixcoo+0dBvZSFmC8/mTnd11aCUZugHIPe5wGQ+VKNsDS6QkIPTmtKISf6sNx1dJYd7Y+uJbtIAktbqvUMpO4ulydwlMzeEddZGstR1nXnchPeB1e4uuq7pnRcF11xboUtBWqZ2JPNTFnQxsrWWhI4wcr1l/uUvKuVnKemQ+VjRRmOTheYubu7n4NLaoHC30L0Z5Lk+pASaS4wgJV4HU2K8OeeEKkTmTiuEurmFGiobOzMspznbmxCrOkptSD94hmGGqdz5dMJURV1X3HflCidnpyJAmJUXSswixoDNSTkp5QZYyZG0wUU/YcqaO2JqNPbeNKbk55u6wViL0UaKfueYylplc0zpknr9tmBqC1kzq6oqQte/DZiqGHpHitJ9cmdnF13VDN4RfaRI5pTst+INFoNlJGEQbJDkcB8/PUFpPzzGU+Yen8qYquxo8N/puuuBstc59OBQSrHd3x03wL3NluSO+En34TGr4qMv/+CY376uhuxUyAO2Bw1qqxkGJ3nw+f4pJQwp9y8QlzuFlFuOynOXoptpOM4vfmkCExlckMKiwWfOsAhB+rxZa6yxfOXlff7XvT2GoUMhQpEKRdCZa8w89u998FvwNztUBke/grqytIsFH3f/qfDWxyf46PjgrvQ8+Od0aG34hpwemFLi/+Ab+SP8iFjYs+A6qBw7ULz/uvThttZy394O1jeIBZNIaSELsO/4N5ccfd8xuAFFQhmbM0aWY3/xEBO/65UfJOWNptt2nJ2d8GuP/GcZ6AaURSmR+z7rB+LVM4xR1KsdVsdHgGK7vyd0ReZbhYKSjY5iBauyaMUK0spgtOV3+J7TU4SuqSwXL93DdvB0g1AArjtFZ7HOsSAue6gx5+RrLUq25UCJKpRpP8eJT1RHzlaJEZVyPUBlMVV9tyX+Wb+MsagoB0QZUQVYBdH1BKMgyqaXksgYaZ3bwc489HZPPMnBOXxw0otdyZo3SdR7gTEwr5VGmaxOXTA1Z8DyJiG6biFb6nKguEFqMCZMBRGANOKxPPTQg7x67TXc0OGH7VjJr7Tmf4t/jNZYFIaUFFu/QSkHyvMj6utGTC0WC/6Y+jA/dPIH8dGhKEaccPhft7xAzLpTCvin/RE+eWKKaKMJKaDQ+d0T/831D7NYLDOmHrwFU2nE1F+7/Efp+46PDh3/cbvImGpuw1SzWhJjom4VOxKsxQ3dHTG17gdicGgDO6sduq1k8hXv6m6Y+vGwzphSfOczP4g2FqMtdVVxenpKZS22qrh4+TKLIdD1Xqrwu1OJBRk1Hi4oWQXRe9ATY6S1AqOJgQlTTMbF6PXHyHs/+Xeo6hoVE7/5eX9RDmn7+ph6g7ThRMidX6obh/QHe9R1w2q54vDohK47zGxgztIxhpQXAmPFJXygr9imwNn6dLRKRwuT3KgnJqos7FYmnliCsDNXXsaEiGwiIQRicAzestl0nNWKuq0w1hBDYLvtWK4WuMHhXcdDD9zPA/ffj3cDZy9+mHX1tUK9RUDlQrBcRbzenYJkSimMNtRVTaOgd2JlShWteDveD9iq5qeXf5K/9MwPobTli6uP8tfv+/O5irvHB/F6jLVcXHyEn1x+K1+ePsLOzh5aaZxPuCAuZUmTVkpRL1p+99oyDBY3U/00vabZ/gDPvue/4LFf/z76wXOz3cHW0nfBo+mD4okn/y4xej713u+EFKlsTd00HHmrY+vBAAAgAElEQVTpfhdCQnFGSpHFYkVz8SJVlelDNUnqGKOpqgW//8IuPkTc4Pk3GO6//irJe+h7Oq3ou5520bC7t+Lq1ZfoeocPokmUoifVNUV7yvuAUlP/8uIdeu8IbiBF8WzmHLxkytRZbkN61AzbjmGzIbiBEDxT8sQ754oRnBMLSmuPrSqpUagbbh6d8B3P/33BVH52oY5FEXeOqd3VPlsfONuc5YSQYjVmGjUfrlU+bCernhmmUh5TwVWMjDHCGDyDD2y2HWenirqtM6b8eUx1jgcfvJ9Xrl7FuYGz06Pp4IuR7372H7CsG6E0leJ77/um8RCV6nErmKpb+vRn+UP2mCEMozyMxmBNxb+oPB9q9lC64kIf2GvMOUyV+pD/+pUfISXYu3zPm8LU9579s1zh7vjE438BEFVfU1e4EOj6nm7wGK+xlaTRBjRDAB/kcDDZEC2YCi4QgkOFxIY1KUXa5ZLV7v4dMfX+Z78freHBB+7ja4NU5W+3PeuqyftgpNuKN9W2Dbt7O1x95SW6QWK51hhSdMS6Hh0l74MwLkrWz22YykbDNP96ln0m1B0Jhu2WYbshDAP3vvZXSSR+491/8XXX9xt3bEwysSHI5u28Y+gdwQ/EKEGmUjWbPfXRhdZKvAJdVYRBGr6MfYvHjJ0cZyGCG1AqkYwVaypJAFb410lRNYFYtBGp58iaN5vNBh07Ll0+GL2XEMRdH4aBwTlO1xv+4qU/wQubF/hLZ7+J2m5HugGlhGsUTk9S5gpdkAHbdVu+xFiiiQyrltBWlP4qX79VWAdfcO0H2PSRhKOqAt/+1A/y1x/4ZlDSnzol6Wlt64rlsmXlK2qVeP7wj/B5j/5clsVuJA00v7FKib47A6SFaAhBLNroGZLnsV//PpwPJKWo2wVFdVXrTF0qLVklIaAVhOjxTosUh1FUlaGqGk7aGrO3x8HODsvlHj5XxyptMl2gMAYeuP8+KluhULw3JrqH7sNlyjFEPwrJ+Rg5O74uEjfeM/QQgiMul9i6orI2pyEW2lRkI6zR1NWS2DSjeJBkPAk1uFguhT/OY9F1G4mnObGwFeKeS2XyO+eaWqrmdtNa4XIySHQDMfjR+yvxgxIfIGc+WWPRtiIMA8PQTR65/EimtXJ2UPZmk7W5mDILECtFUkWiJuVPyMHuGInBEVPLZrNGx+0MU2GGKccwOM7Wa5q2pW0XJIoeVcGMfE7KOP4rL/5Dvu/RPzX790TXdTjn+dEUGXLigcRMvNAsseKg2efH+hskNP/VSz/Ct+NxrsP7YTx8rbXYpqEyhlUjmDo8XXNlb/9NYep3PPs/8olH/3NC9LjkQCvpwqg0TdOSKErliMemcjvf2zDl0EYSL6pKml/Vdc3qDpj6vCf/Ds7Wt2EqxkjX9RlT0ilxwlTg9OQGru8EU0pKIJarJVVTZ0xFSLkMA4nhWGOoq4pYN7N9TY/pwYvlEmtrEgrvPX2/wbuB4N1YJ2NNxRe//D8D33nH9f3GhY0UPlcWWvCewQ2kkKtR9bT4R/cN0coxWtNUNUlpaSnpBkyWHhi5QyUvhRaaQtzxAEGPB8fIs2f/RRUOL+VaBS9BwK7viMPA2ckJIbcHrWw1LoTBOfzpKT4WWsVm+YJ5tXzmYVURS8wcdw4qOicgUmqSxC7PJ78vlIAbJKgYQ6SqxAWtqiofkMIba2eorEFHT3LS/0AB1liqqiEmySuXG0sQ0vsgPHMKECWlMXrFkA90pQ3WGJxLlBatRaAuRam8VVa41ZBzyk1lMLaiqRus9hhjsdbStAvoZBPUNseOiCgii7ZluVhgbYXROjcekr4RIQg95bxnvdnSNKfj4ea9p+/cKM2+s7OSwHEU1dYYRRm1WO7l0qUIUku9yWpnF2NqQoh03Vbolli0oKbGQG27uNsS/6xfcR7vSVPr1bKBSsqqnvABxYJCkzDa0FQNSeux656xBVNqtOaUng6VSMHUtLGXwKzw5erc50n3Ppmfrh8EU6fHon6MUJkle2pwHn96dhumisU7jxVJWYHEK0ZMpSQxwrG74bzW6s6Y6rtuwpStMpXDaGxU1RxT3aeFqRQDipAxJUaY0hZrbO4HQqanJkwlbsWUx1SCobpp8WG4C6YaBFNhhimJ/dwNU21zBimijcI7T5/b+kJiZ7UzNtryPmR6zWArO8OUGg9+UzC1uzNhatvhXS/1PzltX2uLsRVt8/qYesMsLxBLoqoqPCKbHHwu6SeNp6ZwcOJG67y8rbG0yxWDl2yl4DqM1Zgc9EognLdWEqCqK3yXT8XNKYUXU1pjbIW2NVJzKx5O+X3ve7QxDH3g9PSI7b/6FbwPHFy4yHs//32s12s22y2bbcd62/HiK69wcnLCf2mWnCSP1S3aWP6W6ggpkgL84gs/zO998FvGMUgpESg5/GqSsUC8jp857fkGW6MAHyPWlICrRyXNhz7xCzRNLemiSjN4x88/qPgPfuGnOL54Da2ge9xyfOMVzo4PQVccHh2hrVgVq8WS05MjNpsNXd/TNjUHewuayvLJ93w7j/3bvyWAJRG6LV0fxuKvECAFBVHx3if/Nk+//7tG6Zli+RpjWe7s0aRBeOD1GlMtid6hSGiraBcLUvQM/YZXrl6VlqbGYrQ+RyVUdU1VWZqqYbFs2VmtxJIaBk5PTvmt51/AWIO1mic+7wlqWxNj5Oj4jG4YAGkNW9U12pQcf51prJIerNHakroB1wdOjo5xQ5dlKGSNVIg6wzvrmjBljBwEsVSvU8Yw5SDztBmfw9RiyeC9YGroMdZgbMMoRRKlrkXZgqmtYKo/I++GKKUxVYU2Vaa/FGmGSecGVsYydGtOz47Y/uqv4H3k4GLB1IZNt2XTday3W158WTDVtguGwWHrBm2sdE+NnhRCts0i33jz+dl4TJgyGVOJXMVO6S4ITdfKvpPgxb2voKoM7xn+JU3TUFWShDN4x2azxTvH8Q3BVL1cfVqYep//70dMdZ3jfU//PbQxPPeFf5W+D9KHJIcCCqZSCijL7ZiyluVqV/aUO2Dq/c/9PdRiSYqBoV/fAVPxFkxVt2DKCaaOT/mtF16QQ8tonnjP4xlTSTDVD6CEyjuPKTVSw1AwZQRTg58wFaTzZCJQpbtj6u4HitJsVku0Vlzwjk7p0aIqonDF1Z7IajV+mZTmd556NmpD328zTVZhUqkRSUQXcgpoxA8baYVZPKPiKsREcCW1MMt0xET0jqA1ru+yVINm8JGrLzzF7u4uRmmuX7vOK1dfGnOvk5G8+e36jH5zCplPLlkAP3u2xWjLVz/xZ/m5sy1F7VUpxTcfvZipMY1WjPntSmn+7OIRgvaQ4MmbXyQyDirHfZJid0/kF8QbSsStvN+XXHyen3r5ITSR9z2y5fjwOklVJF0zOJHz7pTi9PgIFZ3ISgyOk+0p0bdcunDAE/oaIQWOTzd03QDpKh49plqGEMb6DbLkR13JAtVaoa7cC8sl/UnH6a9fo6pr/HLJ6ssuZApKScDdWpq2RavI6ckpKULTSNOh45OTEfxjoF0mWcYrx0eWqwX3P3i/qMyi8K7j8sVddlY7PPTgfZycbVlvetabHhdC9iB1Tjuuc1xk6m1dty2X7q3Z2d8lBCcW5sxrLPUs75grrzWtFE1bZa8sjZIs3/fon0FrxXc9/0Oz3xkZCpLSUNVsNhv6vhNMhUoEIHOsMXovsSjSeUwVTjopUIkwJJJJOeXYQggjpnzBlDIZU0+zu7OL0Yrr167xyisvjRXgSTfcOLzJdnNGvxEKCUz+U+ZB1s/LB1/LYpwfNbafvROmRk8pJQ4uXBw3vvK7R/aPjvL+j578DHErRq4Lia2LaCK79ZbjQ/dpY+orT/8xzz73Isdngqnm5b/Ep979HXmuwm2YUlqdw9TOzg6L5ZK+7yHl5AJjCcHzvk9Jmq5qRIq+bRuMCpwen5Biomla6rqeYWrKAJwwpSZM7Sy5/4H7RW5egXc9ly/sZUxd4eSsy5jqMqbMDFPNDFMyvnW7mDDlM6a0Hp/jbph6Aw9lSg8bVUSZnR0lvJZPlPGQyIOQlKT7DV0vWSoxEp3DJz16KDHEko+Cc7245pApC8Oo6ZSi0GwwBpIqW2GrenwGbS11s6CqF1RVQwLOTs9wg2z0WmswlsrWDLnwcdEuUVastFrVaCUUTlU12CpOfLYCW9cUMcJSBwFqXKCiUGqo6ma0pEcyQQvfGr3Edbpe+FFQ4n1phbYtEUmd9FH6P5OmzKbdZUNdV9Jspx+yBlDEd53EqIaBvu8ZhkEkLTKQlVYEn/ApkkKQOoMg4oPGmlFdOIT1OKuFqpD/MlrKxWoWikLWhXM+Z7IUukLnbDaxdksRnzYaqxDFYSU8re97tusNWonUxWopFmdTV9w8Xo96bkXtp9BFRb5+TLvNlEfKvH1ZkT688wobYdoUgZEpHp86Td9Ps/GXZCyFMiZjSrh4wZSMe8oej7S5jbihF706lTFlZ5iKURIkMu1cmAhpC4tshNZmPLWiapuUYMr53M8kY6pqGExHSrBYLFCmzvHRGq0SJm+otqpnmCoKE3fG1Ha7yZjS5zGVx00pNWYxdV1PN0jPdxF9LZiqiUP8tDHV9T39LZhanxzL2r4Dpuq6uiOmuqEfp7hgalREKPN7DlMqYyoIpkoyUs54LB6oYEqexSpF1dTgXMZUx3azQZSIG1bLmsqajKkzKWAcMTVlSZ7HlHyuNoakpwMkwV0x9QYeCqw2W5no2pbjY8bVjkN17jCJKXeY0walLN6dkaK0CU05cIsqwTs1BdDdkF1Fk3tnLBiGQeQ5StwgKVTU2LqhqiVl1tiKmCLWVixWe1y+537aRrJHum3HarEaU1SjrrN8V8R1Wy4c7PNbx88TQuRPpZDVh4GrN/lWGdVxLF557rlxck3OxVdKCoiWD9zDK5/4WZqmZbW7S4p6OnhTyvLWspnf+54vZxh6vrrvePGBJY8/LPyqrlu0aUiuw/UdJb1xdHv3d6jrml+88S66vuP37T9PSop//av/iseTHFAhBPrBEYO0KW4raenb912mHaWgSzoyOqw1+Z31uJhKW+SUg7ApKmJlUUHSfoP3eOfG3+u2A13X5U1d5zRtm199AlEqXeY0GKNIAXzfcXh4xNlmS9OIyu3eqmbVNpxterZdhw8SDyvxh5h1p5z3Y2xvvgbTLUB9R11qMjLGZ1PTJin/lPL/0ogpkmzKaI0yFu8le0gzw5SeGiyJ1McMUyZjatlK+r5zpEFiVmQjwNqaqlnQNAu0qYgpYW3FcmcPfe8DtLXUQ3TbfoYpI5jK2Uiu67iwv4+P0tqXWNaXvN+rL7xwDlNmrJy/HVM3blzH5rqv9fGxHIJlHMteE8XjPn7oS+ltT7/oeM/wC9RNPWEqdG+IKa0MrzZfxqmCo8pwLSx4tX4X3bKjNwOXrv447/r1/04wtVzy9Pv+smCql4O9XTQjpvYOP4m59z+8I6Y+/5N/Wz4/KkIVIIScfeXRKo7NwrrtQLeVeI82eoxzSNwmkqzJmMpenVaYXBTsu47Dw8OMqZoH7rvC3qphtSiY2uJzTGbCVBwVAkrSSB7mGa5KAfHrY+quB0qbrsrAR2m9ub/NxVaLx1BBob29LehmjOH+V5+lqRvaxYr2kS9h31jcsJsVUyXIA+I6tYsdjm5eY316OGHOGOndvFqirIYO+sEBZBcY2uUu99z/KIvVXt5gItZoVjt7vOvhK+zvtDS1pbJWMjOUDMq263mpadnd3eW+e67wyMP38+jNJzg8OuJjP/ujZbWSIGv8qPGkrppmRqdkwi8HQa/+5sezjEYeozQV2RU3tXCrL//6z0prT+954H1fSfCevles1xsO978FdSAb881nfhFdl8Bk5MV1hdlabK3ZrVt+rTuATjZrlzPdtFbUlaJaLjOn7jk+PJaApVYkDfs3n6Q6rQkAaR/96qtgpfD0Z96j0DrxVU+eSmOdvgcUPnrqeoHrOpGriZHr16+DMnif8K4fLc0SkC1/fPCjXpIxOhe2KkxdU7etFJ1pw9A7Xnr5qmx+2qBIbE5P2Gw7fHCzwyEbB7kATt7bjLxQAcDdl/7n5moXLY2VtSwSLDrLXIDyiu96/h+MFvQcU8ZYmrqmXe7QLnfY1xVutSspoEzyIlob2uUORzdfY316NH6u0oa6qQVTpgc1w1T04KFd7HLPfRlTeeO1xrDa2eVdD3/RhCkjm5lijqmG3d097rv3Co88fB/Xbx5xeHjM0eFNygv9/PVH8pqYMFU8lDthqso1RG8KU88+M2Lq//EPjPeQeMwOSsHvu/dFlqtdShfIlBK/evIEZmt55PPew0yOk8HHbLBIXdyrlz6Ye8jnWpwnP05lDLUS+aD9dGmGqYR+9pfAGhaJrBSh0VVNT8EU+LikqSND1+GHgao2XL92A5TGB1FUV2rqWVQwpE3GlNajAaeN1G2ZprkFU56XXnk1Y0pnTJ2y2WxxwU3eGkJV52GWuJ0qRvFk4Mjf3uKBsrr8/mlBZk6W8QMjdWzxbsA7yQixxvL1B3+Sqm54fHchwnUous2God8QvPCX3nmhAVFiCYWi+itX9J5+u831ESEfQHNKIOQiqg5nK5xznB1do64q6qYl+RWHhwqjJEWyqa3wnAp2dnZQydNYRa1riJ6m0iwXDV/xgT/Mz//yT1DK5sbCuxklkD11Ct0ne1ikrps8KeJxjVbofECVwhqDbhpsrIghcu2pf5klxWM++ORzSxrflIEmn1cC7WoaEBKJf719v9QF+IFh6DE5KyqlxBftfJJfuvkYKMWX7D9NZ2yWeFAsuQYDpEE25m9JUeiHBzXm+ROaPPbaGqKpsCliUyRcfILXXruGrWouXrqE0S1uGHIDJ02KmljqRmabRimuWiwW7O/v8cD996FNzeA8167dwGU6TmuDz1lFRmtCnOJ3KUlwFlU6PQp9RppRYLmA9E4y5p/L6571C/zp/PXIeOXN8aHjn6ZrWvzg8NEhCR8VbbugqhsWi2UWWNV0W+miF3wvG4wLU/Hs62FqI4V40ss8ZDpFPjvFgBu2E6a84+zwNaqqpmkakt+ZYSrdgqndjCmodZUxZVguG7pO3ielxJff9xK/dOOx33ZMee/uiKlfOXo3i+EWTCnB1HNPPsnDT7w731Nws1zt4irJnjJVhckPmlIkLrMRoxTOOenemDG1Wq7GSEBCas6KHP+nqi8lasHUY2cfp9fbrIwQ0T5lTFWCKdUKm+C8JCbpSIwaFdVs7NT4uYtlK5i67z60rRhcyJgaMqY03kUUacSUj6I5JjplEu8sG4ufH+JpJov0VsUhi4VQNi5JD04jCKytJCVNi0iaNjZ3/KuwRmQFhr7Du1JB20mDHleyNzR+6InBkfuKjYWPMURc14/c45ianCARCa7H9R3GWLz3bE8Pccbi2lYUPVNWqE2enWWLSOjnTJLgxL2sFD7n6VdZVkCbuUz87dbTxPbN/66om3oMnM64QSac5BTNbJWVidFGj9xl8aR0DiZro8d0WUVRo5W0znlxKEgfb60NxtlcP0NezonFakXbrQBoFyvWthKtJxRNuyDkBaVSRJH7kiD9psv7eO9Q+bAw2es4OzmhqhsOLuxT2XqKzSRIOqGSQqmITjlHSSlC3kWXyyWr5YILBxeIiAQMaLyPKJVkTYWEJo1qzs6FsU6ClEAnSLI5Dd2WGHw+bFKOA2S5hXfQVd+CKYqtgARjpcNoQAfRX9LGjJ3+bKY8hl6MKe+2OXMyYypnd3nXyVggm0fZQGPMmMqfNxVDioEY/IAbtoKpkDFlK3xTMJWVhKNnZ7UgpZALgU3GVMJUGu8cikhlJK03+oli0pn+eidiqjQfKyfWeUyZGaYQKRgp6MFYh3krmHIOlfW7jFGEgGCqqWeYyocBSdayiuio0TpN91QyKEu1EExdOCAmxXrbM2EqSuiiYCrXdCVfWoeEaT0qhUIzdB0xOko/FltLVuJbll6B8wqy40inRAqBr1t8Pb5yY9ZXVdWQpChqfbIleNEDahcKpXu86khBJG201tRVTfBbQhD9fhQ0bSMbYgYA2RsKwY+WDii86+m3p2gFpqpIwTEMW0K/FoClJDUzfYd3Kyk0Mobq6IixNWpt2XZd1gCTynfRuWF2mMhB2nzoMdxPP48C6g89JmOf3VBjZcPsP/Zs1iOLkxupppa2ZVOtP/joSN8MP/18WafnrgK4NLcQMppKLYu49BPdaHPuOzRZ6lvu9Rvhi9nfl/s8yRcTX3pppCplOmcubZqSK1JKPPTEEwC8+NSneOjxd/PSM0+hVOLK73yQvu9wbuDo8Ab3Xr5v5KdjSuiY6S+tiDHXJJRtI7vqTduQUmCz6Vmvt6PYXowelSKrpkERUES0Nfj1hpQku8bWzZi2jbacHL7M0J0QnASGl7t7VM2Sql7dfYl/1q9Jn2q6ZNyfX30F965/XDoeNrLhSf/0SPSO9YlkVQmm9HlMpZR1qGqC6zKmJD7StE3m38ljdhdMbTKmbE2KjmHbEfoztBU6RDC1xXmflYE11dHhDFMV224rmHKOUitBUiM9UzA1Ulwwumu3YmoUgXwDTMk7JTBa6mTysM6vN8LUy889TcHUg48/IZiyGVOp4XZnN9P9MBblppTEsL4LpsqDXb38NTx8/DMUODsn0krODxwd3uTee65kTHlilvRXShGVRic9Fn3DDFONSMzfFVNphqmNGGFaga2anG2oQRnBVD/H1C5VvaSqd153dd/1QHnqV/5ZmYopjpYXwRgsRHjskZXJA33pC79qDOgsFw1O9wyIF64iaA11BZsYxo1N5zzpqq7zoSKfHUKg266FWstuWCQQXE8MDbauCZszgnN4Y2j3L+QfS1grfQeCT3gfOTxeE7yjri27qyUo2G47ztbSyrPfbqmbBqNMeRUK4OsPPpoX7vSeIUWiy6d/PpAWX/P4yE32H3t+LOIrvyeHSCoDepuVVi49UgOK5kOPjtxm/7HnRtpRYghiNGgU0kFVs/jQo+Ozz7euSKL/2PPT4k7nF/zUyCqRIlx9Xj7LGMvLzz+L0rLBOedH/nvoB9abtWg45YUS87MRM7WhJ6u0MhWHN29yfHjIk7Xl4MIlFssdFouWoZeq6eh6qhSplOisbbdb8WRTzMVlMsA6t11d7hwQfI/rNkCiOztBKXVXqe3PxSU9S8rmCQVbBVO/ePMxIPGll18Y5y0ET/BOHLJcp7FsK5w2DHn+lZphal5boGeYshPcQwx0282EKSS2GfxA9E4wtRaseG1o97xI7uXkF7H+wYUIR2tCcNR1dR5TZ2tpj7u3R13XjGKI891e3Vp2cB5T4tVIC42CqZS4DVNyr+mLN4OpQricCzjndfvS00/lbNVyH8VDhRK7FVMpkZI5jymm5JBSo1Uw9VtPf2qkOR+9bPPPZkyZgqme9WY99psHMtWdQGXqS80xpTm8ecjxzSPB1MW7YEoLU7DdboleYnCpTEwCbWtM3bLcPSD4boapU9SOYrH7FuXrjTbjpl7mpVSfgEhFT/OlxkGkyDf4QEKCcNYqYlA4ByZn+RirUMM03eUEHlNtldgvWktqrVJqkmEmi6xFaVyThl60pJKVz87zOrrSWUlTijIl0LftB2KMbLuezbZju92QcrBxXrV7/prRBGR7JonQY4wJlaLoYs2sMJOl+kmMbnj5/flV7leu4q5DLn4rP5ffv4ACpVAzXrMs1vKzaaTGpkU+OpvlPuVHTH7HBEmVTKnZ5yYJIKfRMky5IVNPoSRL0HN6HgGSUhLok2r5ns16A0qkty9c9BxcuEzRHBr6Hu2GrMMkFmpVyUaWEE2wGOK4kS53dnH9muh7cglqziJ8/e5yn4vLaMu53Wgce/lmoZnr3AFxjqmw7XKXx6y7ZBTRKpxPgietMEah4gxTOtcwzAxCsTtESeA8ptKIp3OYsnZMMxVMTM+NIqfLitL4tiuY6th0Hdvtlt2dHZkPNcf1/Hp9TEnJTKRQm28npkqpFLxJTDF5HXOjcga32WfOYkNpesek0igrD1JsKOOelS6QU068lX58wImVYPSE5qoCznmGvpdmZyoxOMeFi5c4uHCPYMoFhq5HDwPOg4tiQFR1LXNdjG8vcUutCqbOiGEgpTCGAUhvNYZSN+e/URZEPvrLhl8W6fS+CRVFEiUhvKIxisoqBicKqtYorMmSGhTqTo0LJAE6LyJSGq1hFKO2k1jUUvyU3AA+5Fz8srflBZCypLeSjCiT9bQ22z5vhgNd1+PdQPOhR2kWS+LHr45BTaUU7mdeoFiTsrbmIB3nGYisf/Lpkfc3RrP4g4+Pi2D7U89QQgByn3gOBPM41fw6+4mnMoinzzVGaIHFhx6l/+hzM7c60n3sufyZ2eqa3yzd/mWhHTTTXFZf/Qj9x57PIyluUErklgUSGCyp0EPfo9X5rB3G50njs0Sd8MPA6dkZh9eviwSFFtQtVzs5ddHl+ejpe0dUGtu2NMt9fAijNpLrhvzskdXODn7YByIxSfaKzRIh76RLMDWN+ovPPJW/kkEvrXT/1cl7+cA9L4ybdkqR7WZLdF4k1NUMU54JUxa0vxVTxfOcvEqYYQrOGSDnMBUKpspagtFVyP00YozS0yMlNl2HG/w5TMmhr0aPA2Yb962YKiOTv5eySGSI8RymjDUjpmRD/vQxBel1MWUUpKLKkTH1wlOfOoepBx9/9x3ueTumXn7m6RFTKaXxEEkkfuXoMb700guzvVRLszHvR+3DohRd5m0al/K+4IaB09NTDm8UTMkaEEx5nPd0fY8fevrBE5XCnMNUoK4qhqKbpxKrVcZUisQkBabSovstHiglgDZaUee+ZqSAhp9+nsnGEnfakL0HJZNRMnAm4zi7s1YqXRMwDAOszyR/3JSqcsnw6LbbMZg/TZZMkPeOIQRK9sLe/gVCjFm+fcPh0U2C64HIzu6BmLTZElBKjcFka5QJd+oAACAASURBVCvcz3ySZmeHg6/7fE4/8qkZBXT+4Jw7bndaUaJNJdbx9p/8BiUbw1rD6muekOKpjz5LCIkY0rlNf7RYb/kgxXlQhJwq6n7i6XOH/OIPvgvFxDMrxfgeMaV8+KTJg0vMCgfLcQz+o89N/1Cu8RCVvHjJOFF0XZcD9oYQrGTezNIaZxPG2XpLt9nknhCKw5uH+BCp6pq+j/RdR993tFbTIRuWHgZ0PJ4syujxuVVBZTTWKnb29lju7BQH65yn9k65RrXtjKOqqs5har4IbA7ygnjUJkViCplCCXnjjKQo6eCFP9BWCkkTSjB1thZM2bw5qSI+WDA164uR1413jiHOMHVwkRCkm2O/3XB4eIPgM6Z2LmRMkTEloqMFUxKLMCwXDdbqtwVTkM5hqqrs6Km8HZiSx5owZazGnsOU4bXfem6itOJ5b540TeUcU8DtmEKAqPQMUxRMmZyRdQumbOnBInfabNZ02+2dMdUF+r6j73tao+lSTrUfHDqcTM8ZJO6ljYGMqdXeHoudEjMpmb6vj6m7HijWGpocgJZD4/w1fGz+vTR6dou2QVU1cZD0vd4rtFqSTEW9mJr0BGVQuhqlAIqi5UQqS4Bo8pDT7I/CuUHEEEPELHdomgXLnT1svcBtTnMTnY5uu8b1W0iBpl5g6ya7binTX2L1ZmdIXPaffIadr30365985pzW0jzDYWSS8nuP/ptS1F/12GzJFPDIq3UffTZ7bSYH/GT06g8+SvdTz45SHPGOE3cLBXWHy/14PmDyE8wpqAS0X/2u8ff7j5V4TgkwFq8OzqFjvIGoQE8UAflQHmQTMzHfK6dr5mp9nYvWtNYiWBcjWhe9Lil+W65WrFYVfd/T9z0HB7ucrcVLGXwY42KJbJFXuTFZJcWq2kisJoaQa57i+Wd/B1zWmnGjevHpp26jB8crwS9cewSAD9zzAou2pa8qoiuY0hOmltnK1oqgDUq9DqbKjZWaYer8GAmmNDYGzGKHpmlZ7uxjqxbnzvBO0tK77eYWTLWTBZ3imJ5cnAMRYfTUdYXz4S1hiqTuiKmxNfAdMAVZjeMzxBTlgLkDpgrtVH4/jZ/95jA11X6U+2VMeYfWkVQU2uPU4mGq4cl1KbnIVzDVCKa0YblaCqa6gX7ImDrr6AdP70T+qBySRkvBuNEWU1XEWNonKKIPeD/c1TuBN/JQZgtvthzH/xuHJFu6Kru1VVVh6gY1OFLs6fqQ3V2L6OwrCOBDFifL2TqjVV34WiVSkCmmyeQsEwS4LGsQQ8S0C2y7xDQLaf3qhpzD7fBDj+t7UpIcdV1V6KQAkUAoedjGmOzCS6GkUtJKMyqV89qnw+yc5z+3LMdVNje2pq+KdZaQIPrIb2d5aWuLpTWJw41xkJRu+5gyHZKGnf+eZpaXKvMzswRntMPYSjdBJjCK1NNkZaXpvuV+43sjh0bverSOYwEaKdeCKHmHaHROH7ZjK1tVvBdK7UGibopkh5YCLa9IypJcPlBmlce2knROrS2llQIpEbwjuD4fancYsM/hpdXtq+KNMGW0oqospmlQzmdMSbdDRcYUQFD4qLKIYsEUE6ay56ZHGpLxz4gplzEV0wxTks48YWoQTA09KUmPDW3rsRMgioypIAWqSmVBxd8+TBWK7FZMKSDmivXfTkwxw9QU4H+TmJp5GiOmtKIfpLwhmnLoW1SMpFxjFbXJ6cNkRYtbMSUfUjcNormvZphyJBOz2kDKqfgRW1UZU4aYfGniKJgaetJtmb/nrzeUr+9+6tnpUL3tPuen1xrNztc+Qfz4VZqdfZy2dCdHHB8f3+mXxyM5RjdatH5wBOVvO/VLULpMdCLRbdYMfUfTLLhw6QpJwXp9wqbfANJzfnA93mU9fyQ1z9axHF+gU+6nEmkXOyP9Fv4/9t792bLkKhP7Vube+5xzbz3U3ZJaz+7q7pJA0mCC8RDMYE9gGykkRiMQCNAwYAEGD4zB4xjH/Ob/wI6wI4gJGGxmTAwOGBB6QSOhBy+PQQLxGL1A6ne3+l1VXXUf57H3zszlH1a+9j7n3qquPtV1u8kvorvOPWfv3PlY314rV65c6RwOP/4Azr7nG1BpjcOPP4BV240sGM6bMWjW6lMPJ+HZgHBeCXrpPSJC/4kHRanUFabvOIf2M496S89Fqz75e3N2BXL4OmUmHg0fOqgPAZi+49xgaHyL4myt+8wjCNFfIeTUwnkrSmaPWmtJ5QFAUQ9TaTmBEhWcd6/Akk8sZ9EbfxqhFqLDMdrlCpcuXsKtt4VzVzpcfPZZtK0FqwrNzmmQqsBWwl271VJkhyHnUSAdr7A8PABbv8tYXyUy/kVGXDxm7165Bk5NJ5I+fXLqLHqqseIr2LuyjzVtmb2phFM2uXTNcZxKRs5qMUenM04BmC/2sWiXAAVOSeqejZwiSXIpC/uM6WzXu9/Ebdd1PWazKSqt0XX98+JUINTz4VSlVeSUJMzEDeFUbngTkT90JpQkayaBU2HmEjj1+cvnYK3D25ov+SSMnlOd55RSiVNax9kWyMgMxWr0pgeD/Z4gz6nVCpcuXMStr1SwhtF3HS4+8yzazoKpQrN7GkRalL0PBwd81Jq1Yng4B2t7LOcHYCPrYdedbfh1b/tvMJB47+t9/Muf8X0plkGlFM6+501glpfwwcEcr731Erq+k9BeH+IXfHBxQ1OcePjjW5nltLAwCwnuUgpTRpcsKz8tJPh0LKsFLDsYx5icfgUcJIrB9J0PQyY/iHKGiGhwBzYS+eWsBVciZErJTm1rHZ776N+gqiqcfc+bsQOJSNr/nQekHchmcNEXTLGt14qg8RUR6rffCSJJgd985x0x3BYsbmrngOWnHs5y7mTrUp4UnL1YEg8DURmLTz7sfwv9miiaT7ulTvKHIsLsXeekfOdQPVDBaA1rGa0/RzwonMpVsMag9pkLdnd347NN38cZCnzeKTCjNx329vYxme4CkPNV2tVCFqIBVItD1PU0zlStM+j6EBFIAFv0bYt2ucTB3mWcOXtGIqZO2AwlKBQA3n0g9U9r44lTs1kDZjlz5NJzz4gLt+thTRvPKzmaUzb5+5VKMmCHVnbiFEdXGIETp5yDYSeccrLj3vQt6rqRVD4cDkYTsrJjsJUXlHNyzIUxxidUVOg6A2sXqKoKs9kEp6opus5g1fY3jFPs+90RQfv1nLquBpySNdfr51T67flxSlcy/krJPrnEKX/QmHcxVa4WTlU1munE78Ynf3yHiTOUMBOBk0ixvb19TGanAJAES6wWWC5XcJxxSgYO1ll0XQqcgPOcWq2EU2dOS2JXXG/6+rF2Dh0TF9Tg04RQfOkDkCiFbgXrNzblfjf26pzzAgednwl8gAuheekZY9EyfQ/yKbJB8GG8LlpRnPk/OWT79CWFKA7xF4b/KM6IJAGdkVMNK43ZtJG8QTZcsW7hUNZpawbY2LBkIZIDD144zluUoSytw8tHhM+p5P+Mi+4xAi4+PT53jQjh74wsqU5CAMcyk3MYuhbqqoKp/W5hZgBzhDDGppHjYitdeYsqtSn42YF0zgN732+7kmR7pLQcL2yMP7DIwS6X6NsuVjqc3hjdd+zQrhaSkqRdoOsaMBjKnayw4eHbZSzPR3HKJxZtJbkn3CZOjUYwvuR4A6dYvL0IATOjn/0lkVP+3BZm51PKuxGnQjkqti242XTgk19AD+k7xpwiohvGqfzik8Yp+O8ip6oqm3jO/T2eU94lXulqnVOccaoWQ0SR8gksVyCqPKdkbcs6B7ti4VTgox+rsF4lnFomTvWeU/p6sw3Hnsg+EPCGv/P2uAta+d2y9KRo8f4dBt/28Gswv7wHZ0xclEuC7b/Izan8MT4yI1qefnSGkRLrloqxVlJGN3IsLIc9KtZnOeY0eEEyiFQU/PBS0zociSmx4s3b7wBAaNsOSsnxmmff8yY5+vQTD3q3wdBNMVCWoW1J8kbtTX8RActPPuyFk7L75M+QOkZrhek770IgVvvpR2KqCQmxHD4n1IngA0zG8MTNusYLtXRa2HW/9MEEBODL39HhG7/+Omi/+LsHSURISmEynWEymYhwQnbPh9ltCGeUZwhRwKKs2naFVbuC1jUci489KFlnW79+IhvP6qaG1jUonP4HoGvl1EtjOjl/xxo55+MEIQ03x7BTRYQnHnwQRBIhJYuuhG+7RdzN1omScdZknAov8qzggeGXv+BcsP2zinglcBSnyHOqqlFN5CiIkH3ahczhG+4kRVlq/MAp7f+TtD3hXZBzqm4qdB2h683WOcXxhX88p5RWkr2ZpX9fDE4hGxldV6htFQ3bvWAsKYXJdJo4xfDHZsMHvmR9pQjNpE6cWrVYrVbQVeNnYlY4xQzXtmC3iq7Cuq6hqyZ6RAiMrl2hWy1hTIt25TmlrneGsgGhc0KoHMBou9SHZ+bnwK6Dnp0C1wbGGcDsZ0n6/NCOhSD/ixGnejlyryTLNAQsCY/Asx0YpdD3PVy7kqlg38H2HSa7p6A1xRxYs9mO30DGeOqpJ7BaiHXdzU7BGAelHYwRsi0/+XB88tz7/eta41Xf+1aod58XF9i990ubQjTN2AE86rthgyh+HPwep/3pM7OcRWCsQ3fvfdEnXimFptaYvvM8FJFs2vzdh+IOXWucnBrHco52/hZiBurvPCfj+OlHQcQDUkZjINwRXAKfeQzqrXdAKfax+4jugs/95aewu3sKdVXj7//n78CkaXwsfI/FfOE3wiGe0CfHuDqsDpZYzufQdQOQFkvK2Bi40UwmCFEpfdfCKhv7QPmoGGvlfPrDg/2NY3DS8PiDD0QJUCyL2QaMrgM+Pb8dAPAPXvkomBX01HPKGsD2GafoKpwCZC/B+i+5MhhEI5HnFEnyQ7dagZ0swNu+w2THc8rJ4VKBU8yMp596Aqul51S/i4m1UNaCjPLjk568f7CMnDp7WlLid53BatW96Jwi8BqnlK4jp6yx18ypdOImrplTgJxCGjnl5SEcLUwkMxSt5Wh162TP1mI+l9xhkOMAIqeIsVqusFzMoas+ccr/x84lTjmg71c+Mi+dUWOsicrr8HBvg9QMcQ0KJQ3OpnJCx6X+IjzjNE71C3R9K2sWG2Rh3eIYFn50lYMkIE6tTd9ivn85mxoj+naddZj6ZG3WWcwmclBP2y7RtSss5wewxvrke3K4liK/i5Z93HVsmbw0u45x8SN/jd133YOq0rjlu9+M/Y8/IMeCZpshY409KdT4e/lx7bvQK5O335m5BxGFNqZu8VUTQlh0996fd648UwE733V3nMYvPvmQEMNxTI9iPvlQfLrsuFb+BS0up5Q6ItWDvUFhTY/VqkfIuyYL7xogBesYf/xnvwutNf7+330HFGns7Oxif/8A5He+TxpJAGj9voG2baGtk3M2nIP1i7/Bagwnx4HZLzSHg7WkanJ29iR25tFydLOQ8QnAHeffPPhV3jWMxx+8P/tOZEQySXeeU+uk2hyvlD950+/5rIW8A4FhjOdUdhVjzCmTOOXE5Rg55fegBE5p/4ISZ89mTu0fzFFXlezV2plg1fVb51T4fcyp2H8jTqWNn/HBUAqoag3tjzw33vDJOZX4cu2c+pMLb8TfO3M/rDFYLbuYuDK4d4VTIRVPcNFLuP3+/iGIHOqmxsR7aSwbz6lOOEUZp6zMSsRNreAn+jF4QynlD6sTfl0rp67bH3CcnSNnBvhDs4w50roI9w5m6vC+4+EEffTsNOFkhKiNZSwtRbJIzSrtN0p6IibXifPx8LLNlsDRjaeIwqFqsYW5D7XvhUy10qiiH9jFcyliGKH/nHbCDjsx7v7P+jGQd3BxZt2EiJy4mAr4Q5iyXvULrMM9IyLYrMJCLCFMuQPJFSlUWkl7INFCiBaUVCC89BzLgutqtfQLgoiOSmcdHDmwXwtpuy5O5QG/47mu0EymMMaKSwHeGvbhj44l24Lz1pcxFZSShWxZ2JcoKQbHtD1VXftn8EnUJteIzIT2fypF/pAmA+vPsbhaCUB2WZTHzZ3Cg8884hR8GhvEtYmqqqBYQ8XF+BQEEKxq4RTiCyqeypjVccwppShySqzyLXMKmzkVfr1WTgXX7dY55RfZV6tVTJgbAhXCxk12Dj2AqvJnoeScqio0zcTvfpe14r7v/EzSR4iZPhmTxkjoMUvAhXCKJIMzIXFKK1xV6HAVhTKIVPCdlA9SGpWhkIaMopISux9YC8GXPph3rpU6tDA2VGww8IOfiAGXBCr4Yut6As0O+5cv4Iz3SX75a3+CV7/ibjlv3hp03QpKyWae4MYJfoSwwdM/HvCkAxhK1Tj7j98Ea60cj8mM9jOPDevlrWohHCL5xlNy59IX5hMPRuXhC0GYRvtPsd94eEn6QED72/fJQm/cqX9+sOu4+9Qj8fS7SmtMmxqTSYNa94h5nVwSevh6f+4vPol2tcRb7vnWeOBS2IXdtSvfV2K1/f4ff1T8xErhLfd8G6q6Ql03OHXqtBz0RAqKDtG1q7gpyzoXFQfDRx6RuAJsb/w52wTtNBzJ2SHNpAFRFil4rDHz4iPsbcgcJMgl/4kHH8CYUwSxEqXpmzjlFQWt8zNnUVzkXq/VBk5l3CcCXEpSGH6pmwaaWTh15gwm0ylmsxmuXLks/nYXOHUKWiufbklFTuVt2MSp2bQZcIpHdb8eTsV9IlnTr4dTMiaJU3VdQ2kHCjv5HV8Xp/6/Z16PdrXEN02/POSUXecUr2SNSCsFa43nVI3d06fRdQbAEkrNJYeXNnJ0SOCU85xyBmEf04BTnHGqadJG8Kvw6fh9KJympgB8dFfo7iSgQTcEiyHk9tGVhuyT4jgwipSkY1AqCkgmVtgs8AnsE08a0w2/D6WFHUScSl4s5pjMHKqqwl995f/FdCI7SQHg64/9Ab7pG74dzlocHuxhuVjAWpZjiMNxwERof+dBLzyVP8+ZYI2DAaMnwrq4h1mSCGDz9jtF0Xz6EczeeS5eM4xk8XaUF9zuM48icpzTUbDMiNErQcbjIu2gTxItrHXxOAH+ra8izO6F6Aq11th91904tbsj0Sa//xj2en+imxP3VloI5niYk9YaVV3HQ9BAwGqxEOGgZBmGc1QUfDp2r9CWqxUm0xmU0lgczDGfXwH63p9LE8Zb3GGGUyZRAoH8Zkl2cmCbnHBH0JWELfM1EODFxuBlBjkzJueYvEQoyp3wSsUcdIlToQRZ1K+qRoJMxpyijFNjekUDWWbpxmQF55ezny1nfblYHGIy3fHp3eVgq3bVoqU2RgoFTn1x8Y1oJjPPqS62jUAbOcVgdD2DYbLW5MpnffYZorWuxqnQnK1zCm4jp+pKR04pRdfMqc9fuScqECLCd0yeGczQBpyqNBgSgWesw2rVyjHOpxQWB4eYL/YAI6dGRk4xg9nCdG3sp8gpp8DWgJFxSmecOmamcpWd8iEiI81WwjROdrWniUaIiAiLPacB1FUNO2n8uQgchTNEVsWXbvgUhH+ot+JQgtP5H/G7DZcODBQCrO1BtBMP41r5dBQM2YAlu/glp5gxFqQ6WFdBV57cPk+SHGdroY2kmQ7pI/J4ecoUa+g7IoB6sbx6Y0H+JMLcskz3pTYMI0u8cvfXqtAlsf1ZrDx7SyzcmVluYu2reG98pG9HnoBvMmkwMwakIOkyvP/cOetn9gqoK8xms5jmI74wI1H9f+TgFPn9Kg4aqZ+sNTB+uh2sr7QB0Lc7Izr8veT962J1IvZNiO7Lw8xPCmJ0VBiPcQV9hl2Q7H62zmG5XIK9oqmrGraZxPN7hFNBUW3gFI+0yOBx8ltSvEPlNuRUKodIxoxINrkZY7DijFP+dEAiuqGcSn9L3a6FU+sfXixO0QvjFIex5PgOZL+35mhO9fHaxCnOOOXHdcwpuhqnrlOhaL/FP+ikQFAG49cnFu9vQ8ZPibDpTe9PIWP8xVf/CMyM/+wt/wVsbyJxmP2Z8oMFNj+0WT3TfoUccaTi4AYXwgAjhcSQDJ+6qiR9hEuRJo4d/uKLfxhD82azHaDvoZ0Dc50EFIi7WIkA0tqnK4Bfd1EI7rxhFle5ofvEg7H93ScewIAA3lrLdzJnrEmGVvzswxFJPLVACB2UsWjefmcWnuutL06ClAsos8yEHEv4cb07g6sqzN51N3aNgVouMel6ibz51ENQ/9UbYLzRYIyBtQ732Sfj8b/WWOgva4RzS8JzneO4qe5P//LTmEyn+I5/+F554fhsxdaZSJScuEFG8rHlYGCQf3n4/mIiH7J6vCV1s6CVjpxycHj8gfszqy9sTpRx7D2nfv/rr8K3v+pR2dRWT8DMsId91kfOuwNDJ1HGqez1eE2c8i/sccXHnGKOZ933fYe+s1HWJaeUbGT8873zmM3sDeFUrFr0pNw4TgE4hlO0xil5iSO+zNk5sCLUjcbU1iAF6E7WB42xkKVmB0C8IsrP3IRTBn92+a44W/+22x6RfXbe0AJl+cyIfG6vTjhlvaEWOcUZp7J+CUPMNuMURpxyV2XU8TOUsPCUfWf9wtD7WxstKGMlz4/WGk0zwcX7/yNOnT4L5yxmu6ewmB9mykJ2OQcQZHObUgpdK0f+KiUJBSlrdBIX+ds56WgHd7TG9Np0tnMaVTODhM058QeDZCNPJYd5aV35zK8qe0aI3/cnObqU/oVcGhRyALM/8zoObjb1BgafY31HSnUDjaPFv7akFJucs0K+XNx739q1DEbwAsTH+wdrRVBQcirlHz2JrjPY++CXMF8usyR+8Id8MSqlYCEbsbRmMGtMJ3JmhnUOu9/3Vqw++ZD3f1sYvwM5/CfuCQZbi53ZFIcHB7KHpFsivtgGQj8a32C5KvJJEDXCfpTwu/ax8puTAd48kFIh8xYIQNM0MrP3vu1gbQqnxPU3aRp8pf0m/Je3PAnHDmpZeU6l0HrhVHhZ5pxaJU6p2nvRRpzywhUW/B3cWpdHMAB2nlM7Q04RgUjhT6+cT5xqXh6c2tQP18IpIkLfW58hwK5xKsyiKq1gLSRnmz+lczqtwc76VESifKy1+E/zN8H0Bt922yOJU2rEqf0DdG3nOYWMU7Tebl8RglfwmziFcHbLcE1qjGMVStjgEnoquENkMafCo1/4pLw0TA8AKeW8rpAGPQnTeEAAYLIzw3Q6hVIaxvp8Q8FayP3NnHaWBi37+S98ZjD1DIMJAN/6zd8ZH9Otlt6lJfUiJQcLKSWzFh2iwJSKlhW8P/oooSQGoPIwhTwU0V/gvQSEcISLnA4TW5W5I5KNkL1A08/ZIB7JgtFXnLmfRrcGayrUW8tMdO/e+6CIIMkxLZatz9jr67H87ft9eRz3nMC7WvKkjZL0T0XSyhHeVs5aQdqvEhMO+lBKzhNLAvj8F34vHpEQiNB95lEQEZq3n4vng5OuYH//8ZimRiktmYc3yd1NhiLg6w/4M1BIFtuVUtBgsKv8ka0Wyig0PhNzkMnPXjwH5wy+5fR9mwsPin+2I5zSSjgVLHUacQqcHWvLUUGFCCUGb+xDBtC1C3nx+OO6P/fc3bHvJWln4ZS8lyRs9yhOxZodyymGdbTGqc9dugvsHL7ttof9LEg41fUd+rDXhIecGrTNv2fhZ4kI3PFKJRzAFsKWB7PEI3C8QgGiPzdZMhynpMHa0giH9ajMz8iD/t5cuJwH0TQTKKUxmUzD6PhOTH7w6OfNfPRxpnsVI1Tirk0kFfmDoIIVFVOu+PqnmZCf7pI/jTFTdkEY4qAEZNLG3hXDmWLOQ5HDDYT8Sx70X57aO3uA55fvxIER78Um+nd5fCvClJ0h2Zxltkwx3t/5jV7GSC6m2KZsihzHIrhE/aZr2btDYDmLWAwR7y9nSHkh66q1VpLaxfWSVEXG0RPPvD0yPFKPMEUPVngYr5MFiusD/k/5jgH2L9OrciquJ+Rt43VOaZU45fsovmQQZCQsJieeXZ1UPldX4BQQ0+UXTr34nCK/ex4QTpn+KE5d5Z0c28GJU0E+gTRWx3Dq+H0ofkEp1ODRL3zKL7ynxHQgSmdVZ53NSO6GJFDp7xCpUVcN/urLfwRdVZIV1S/+SAr63hMgxV/HBancTKDjO8mxg9IKVV0BpOJ6SlXVqKsa5IMBlEr1DHH0uaDK6WlxNBGuzmfIHD4kOUlvxnBBtGr8P1ketHhdxAZiR//m4Knp+uydkBlQWdnSYSFqj0OIIxB9vs4fVO57Q46miZVPPnqSBiDwN84unQPBWzVQIGXhnAKsAiBrJdbYeASBJpW93BLaTz8ybjyIGKtPPRTrF166FM6HCC5TUnH/xIkBIc6kGGlvwfPh1Gcv3IE30dMDizMtosoxwlVVQVcVzpw5K24070mInAr5wLKNeDzo/NFLXaY38U9ZJ5H9KJ+9dA5V4dRN49SfPXfer5Uw/sGrvo6+k/xcsgae93mQGI4NYP9vaJPzQS4EA1K951bGKXU8p45VKI9+8VPp/IDcb0bZ6ALr4+MlWxHhr77yRzj32rd5pZAaEpTVX37pD6B1BedE2HvTwRkDa5PfPVhSVw8D3axWWp/qvKqbKPghv1B+hkNIXpcL1O53nUelJQR68fEHEZdPB2s7yNwtatDWI2sb/Lib6jwQ1PSRx78jV6w0uNZLN7DR4kJkQ/Qn+3IGXKVg6xGgPJuOHAMa+GlV1j9OERTLC16RJN60PsHgwd6+d5sa3yfjskdvirwJIY4fIa9RuD5ZUidthuKY0VvzgjhV1RX+7Jm78a2veEB2zYfrSSIzJaWNg+tkUb/vO78+InmyHNsYshpPNTyWVut9+IePvwqT6cxzyjwvTtVV7RWehulM4dQWOfW5C3fgOybP+JmKQciNOC73qF4cvGOdy5R74NPxruRjFYr1schjVU9rJE8PSFNm+V4pFfcpOGujZSYpE5TMSHwqAhMVSbbxZ3AgznFSP8Tnv/B7ABjf+s3fGdPYA4g7S8WnizitSy+fNL0ldJLuoQAAIABJREFUklMprdfOqZGJ/xR6xAu+hPoBgE3u3EG1RZyUljBl58Otxy/SEMUE+GmnPywon5mFz6KfEwHY3x/DZsPw+LpwEOLh13Gsx6OaLJrwPYGJPbdCDwz7EqC4JYjYv2D8+MmKAfDnX/wD/L1v/q/hrPO5iDaIfhStTUI86jMOXnfx/jMfdd/NQzCUtsEppZTnlLRYFoE9p/qMUybn1JBPRymTz168Y60eef2IMk5V9fPiFAC/63+oQAunXjinmBl/9MTtkVPf+ooH0kP80z8Xx1byxB2NXDECf3LhKJlIOF6h+P0auc83de+gW+AlCb53ESSEQGiaCazpYUw2Z/XlykE9IUeQzRSIWCQp1DWv2VFWq7dPQlWyKZ6zFk7ZKKDJGmIQ/LkcoZ3RVScLa9bJCZI0flz2vGMRymQRfeXzXdV1jZ77OAtc1/xZ75L/H8tUOfnBfStYXEGpn/wWLAoxNen7dcWcl4VRt/Kot0WiKVproZ+cr56vR/CD+zTYYlYhujYUAKfYj7+kaIkVGBqHR3fr4Boa8WZjY246rE9L8sI51fh9VT3i7f7FY0wfd2nHXdGBU9mZQgMX15ETwU2cEhkKexPqZlI4dYI41bdtXCIY0GC9s9dmn7TWjvU2Hcepq0d5hboMyoxqNft7qHHls/hnv/zVP8b88BCLxSGMMWvTqPg8v73/6EqPGj92Ewx+k3//3LvU6noiCSDrJi52KkrKhUCI56T4qV1Vpe7Jc1WpgbPTR4s4C0vifgip/UGIua2Tv9VHc/iDpkLW5tCSja0mhaaZYPe7zqPvDQ4/fh+syc/5yGkjJVSV9tFOGq3PC+T1eEznH4mzoZvXS8zCecNQ5y8jSn+n/mQwSS4jdgxWHGepUBpVRfjzL/whvuVt/zBFuHh8/j/9XlY4NnwOf2e1p2t4Ed1kbItTs+kMf7n/5sipb3/Vo2BmGGtweHiw9jwc9aLwPAzn18dF2A39GL8jGnBqcL75S4xTdV2j7w26rn3ZcKrvOjlqwDn8yYU3Hj2OAD574c4NvZPXPsnCtXDr6gdsZSMSp3zpUaM6DLVySL7Y+42NSmuo7ECf9eelnb7DxtBg+pn/nqy81OrkPxffoq7qGH0iIYx+Ou0HKUaZ+IaI4aKGpI/TTo8N61Lk/5+/Hwailem/GHGT/TS4NnO6MsupiN3H/jou9sUi8/fFppeGQ+Z6yFu0fi0RcOrdb0aIPz+49z6xlrxlvNHl6NtUVVWsg7U+IajvV+dSPZWSGHvFkohzOtvBl+77LKwxfrFY3Bpaj89cyMd+KPD55r11++KEaZgQYbRlTn3u0l0bH5fWlUJZ436Uv9M6698yTnXdDedUM5lETrWr9kXhlKmrNU6t12/7nLqG5JB+ujX+PhcYzgaOU2gd+2Mlnd9IqHWVLQZmFthGqIFGjAtZg7aEiBBCnO0EoVbJWtJVlVlRfmEpEiTvJC8clE/fBzI7nFEh/wzklVtTf6MxyKfXceqd3Tu+lq3fp5HYPiRjZswSwbsLHVyYsrO/aVA4Dz4G/lCIkMnLHFzt/8p4pP2RqsxiMfHanb6vFXzyTjG/mqZBVVdwVs52MH0f3Z55P4X6ZR8Gss7Z/46TqpuNuGeqcKpwanD1y4NTV1UoUnUaDG4uGMMODBENPhTS2XgoDXkhZEbMCcNIuYhC8fkO6RR/j0zIMSABBWFFmBJTTJoWwt3yoy3JR52oQJZAqtCucGKeyloc/0dRuHLkYstewCRWPu9MRDnIhyf6sWlknQ5uzD+lGHsOPlE3/J39aYdgG2U+9PPRgiEkObj3vtjXw1DSDdYNc3xmVcsxsc7aGLaYomFGBOAkP7v/6E1oaknHsVqusPfbX03yEdfTkAjhCRaKJaUwe+fdWH364ZTSPlxzApH2UhVO/W3hVLtqX1ROyT6kBgCwWq2wXC6fN6e09sdHPE9OHatQXvHdb8H8Ew/GDYYpZjoXAGmYy6JHQpJI5xcB5XrZbVlXBKtCrieXOtiXlQ9/SP0S+j5EkVAUXP98gk/wSPE5wboSq4qyEMRkTaVBQbzWmymxLgOLxUsQB4mKFsVYysPHofUnlkr+HY/aMkI20LHU/NK1Qy15IGv58KelKU6D5y2aVOsU+RP8tcNW+cVZ/0XyzwOL+SI9jAgEDZCcqKkoWdgAUv4mAMtPPoSVJ5pzQiLWOlncwUKL8fR5HaUs9x+fRj2ZxuNpwTixubx2dmaoqrpwKm9q4dRWOWWdw6ptXxCntK7izOj5cOpYhbL83YeS5hp1A0CYvlPSLYAZhx+/3y+Gpb0jch9Fbc4EOMjuevaJ/YbhwEMhCBtoohBGawrik6RUfpp6D4U77uQlyv4b2EZeLZPPrrxWDSQzKHVEJr/AUes72TVHDQNlbRKh2mC1DDjEwKZh5fGfnD75j2GHeixs4Dce1T8vjwDi8Xl/kSLR8hpXG6xANF4Xy+7Op+C+b4kIpEPS0fSfkBGRABiJjBCBoCBrL+wbe9JmKtbYYzklGzKFU7brCqfW7knXFE6tF3+zOXWsQjFm0z6UVHtFyp/O6CvpJNTX5RYSQcSdwoC42Ag/jtKBjKTlQ7syi4myHD/hSNQoyGs+3PRfKIei1UNRYEXTB8spPZvWqhL83rE2a30RpZeyr7LP2FAmsEEsNskQDX/bJPjx0QPrLY2BXDZcKE0CnCoYrKgwfqnf0sNj5qTwm++b/EUWrUamrBzPt4zMkfAU3iFpzNK0XK4UkckI4+8NdQkuGgbEgsuIf1JgzKZ9KB45p1zhVOHUS49Txx+wdcQAhUoc/s59PoWzG0zPozD5Cs3eebccVqXIRw4Zv/EokCI8g9Yeliyj0feREN5qAgBPxjQNTx0ZHhT9zCznxgcfMcWhGD4odd6G34I4bZheR5/4SADl3zQiPPxfXkC6PxoPR4wH1qswjBzKy0WySGIrsh/XhGWt4xEIw3lb8n4aNVk+yJTcRZ8CJ4sqjM9YWCnsZ/AylT2K/Wl240fDu4fEM8Ib3i43F4/5s+KP4lTXttfEqbArnYjQtm3hVOFUfO7N5NRVzpQPmiv70zc4+O+Cf3cwxYI0Ntyy+vQjqaLsFxNJDbo9YOdd51HVkhNo/rsPxNTnqUNi10ftP7SawjkKeanemqLQgf46Cpuv5LvoXw5NyeQ6bkXKNPpAoGMfyY0hcysz4mJk+CIfYMo2G4XZf7QwBkWnaerG6XBWt7V+jUITgizWf5ehTb8oJacEBpfwQCaBzJWd7pL+1xvrxtF6y190FIU4iFbsq/BQ5cc7ti0MWTjmF9l+rSB/kn8WGMvBScB2OOWYwcb4so7nVOVTnVR17c8sKpwqnLoxnLqKQkHquHxwkQQ/bxAH4UpygjxPagiNDKfW0bhH4c/OppSjRhabst4PU20eCr2uKlkoJEq7gUcgf/+YNIO2UhI4zu9LP4+rPBAuhHYRMK5C5i6ON8ku2LWqIkbY5b8xBknvBvULX2/gxLiJeV/GejNi1ta8PkdwbB3+BTL8cdMYjGwgolR5Sr+P+16KzncYU3rRZkUAiKcBnli86JxSKXFm4VThVFb+tjl1/E55zvVrEmJwUHZ+sBWJMDJHLesoCL5vDIuQhiNbjhqj9jOPxMeFJypSgPKpoIOPN8t4SUSYTeXMaoCwWMzBLJEJYYFTeooRsmdGwafUTePwSs/YgQ0QP1L6jjnbZYREkjjQWVs22Rly5cAkS3KUWQrrC2eZ8I6ek4vZoJgjkaw8jkctpzvz2uV/ry3+BkMXiP5a+Unld6VyvF93sJh7BAbe6mhZjtrHyE7ou6aGv6i4GZxiyNqN6dOaaOFUuLdwKtZ2C5w6fg2Fh3cPLZTQwam7cyEZC3kma6Ewr7lTg4aalKOfNgz6wL+bTVGJCMbKyWaxA4K2HU3dQ0WUUhKvPZnAWitnMHd9JrC8NtjhQ1oMywdx7cooAalfRpZE9mIQYRuWJ/23bmnELlynZSqbvTd6bOAgF5R8STH0szx1SEb/ezyACYPzKKIvIz43Iw6Fn8M164t68vIMBx6lF+YYlD1Th/FnxBcukSTPy4nBNG79zUXhVELh1MuPU1fZ2Bj8rDSoD0tNfIhaGtDxdDe3JlIDUucNm5kEP3S7TOM9yQhxKjuIVPFCHc+T4CCU6RrfMwMrijICpc1moQDCYOwDcSncJ6dTyjRfnmetTebPqB/i4GMoJ9HVEf/kaCSN3jupHpwesxl5xfMJ7fimDULI+RXDHxkp7xD7a0cXJKKy7zKSg4HAa8H9fliUL1k6JU/ltrF5a19KW0XQObk/KFF3/MK42SicGlStcOplxqmrr6H4p+YLV3HsMl/dWPcGiZHKJMskRoesWQKjQfI+2dCgIBRB+Jg5LvgB/sxpLxXpGaFk2tgJzHLIk6T2HgrGpprlFpOknxB3APtNZzlXeCShw78zoo86jvP/xQvyH9fBadSzS33/hjKCVI14PaCHLyPULmaL4OzFFod89EbjVF78LlyeW1oc6jCqiL8nvEyyR2VtH94gj81fhDFGKCPg5j67+SickrqnbwqnXvqcuqpCWVtkW5fyI24c/pG0r7eAMNzUM5z6p8NkZMMW4mdZ+FMxkZz85gb3jj/FGPrsB+ssbGcjRYMWjhfkAuktoHCGNXmLS4ez6b/zDWjv/SpSSF1mlvgykyshqymF/k0mRFzMC9cEwV47tjRRaECYWGdGLqQhTHRspQUxI8/YvPcYPIoGShuh0lU0GOv8JSX1cAi2zWCMI5nIH7uKzHrPrgkVDu6VnOCZFZzGkTfx5EShcOrqnDJsEcazcAovGU5d5QjgpG3jjDep4dgghsSgr3VCDhWso8yyCgVmAhLvc5zi2QflUmxoqEzyTnKU1DSVzs+0TnUnBIHIfskXnrKLQwx+zEjKkKRr1vuHf+drqVBfxxhPPhAUxD7QVYXT734TJpMJAIK1Fpc/+tfofMoEIkppK/IqZVZREMQQ6ZMqP+z9JDNDazj2oi8j96GHZ6WwT/ZNpPhuGEYUUZrecx5mGcYpWcGxHUQ+OV9OeE9HpRAjnrLoo/S4fDxTn4QXLQfLbeyDuNkonMI1cSovFNfOqcmkGXBqfjgvnHoROXWV9PW+gvAkyOqd/4tRJwynYb5ComKHlaH4P8TFIQrtzawAhM4OUjus5tBwoyjYa1bUhutp9MXa5ql1GvvfHdgO75H2SqNHyUVH90r5zrE/CpfgfObT8NwoXPHxw5LC8bFEssmtriswxE3R9/3Adxtn75GMyQ4btC7K4ZCwwwsihTf2i69Udidn76kgxLkARcYMSo3jwjRYBAxEXxuV8RcnTI9EFE6tPyw0uXBqY7/4SmV3nlxOXeMaCpIVNCpU2hSenGv+YGEl7RsEn/w9uf4HcyomRJ5kZYb8NqO7kpXgJL9NsqJyL+8GAaZRR/s6KKW9pZLSE1Co37j54dnBAvAWJWFDjrn4CLnWGov93/qqt/aka5w/ITPUb2AZ8bCMUI5SCpNJg1ve+zYwS3joxQ99EY7t2vXJk+vW+uCIykbXRGbO+TZnfZPechiLpRAvC5WldA2P3p7hOZz/Rkg5j7K3bvRWjOUoJy4BoLQmcNJQOLV9Tq3MEu2y3Qqndk+dipza39srnArlHcOpa9jYGKY5+Xeh9PR3/uChXy5YS+Fz6pyhINHoI8VY/HS19E5uccQnUJb0Loq9Z53KBmVkSqWoF4G1djSQPnKGhoagVIAwGutksIyfhdGgxoY6BJdqOJ6YOTvwh9J96QUkfUGepF3X4cKHvoQw9XeD3zntL+DkasnHKPmYGbquUNc16roSy6zt5Vxym59mlzo/1UesphhGmluGzJIFF0A86jRHuAckxBy4CHL5Sf0XXnab3mvS5msyqG4OCqdeEpwye/uFU0jXXAunruHERopazo1HPxvlEAtA2CT8IfwsWESpYjGGYMOUK94TSZOTC4MpauoHIU2c0VE2wL5NMcwR8H7cPF47u4YQv3Oc7hl00FHPibdmpB1eGluf2puEBTnBg3BwCIFMdWGWdNXOGYQXAzuX2kg06OMBKAl+ansoA6C4cWqd4VEYsyYOrCR2/msfvVPX4sOFgzU+T5XLCBUsJM57eWBCxucyADjEHc6USUlOiGGvnxAUTsXvCqeG7X45cOr4fSgbmp1XajCYaScMUjfId5xkKp4dHW2YwUPSBHLQdN8p+aXMgyuEeORjVjaxKFzlyyI/WKQIsDwoM58mpuev7wlIHbCxkzbjqGs5DRTzqGjGQOgHbWJ5CTjYKLjp0iShTFn905tnvRrOwRkLCwJIJSLGefqwMZlzIj3OJYuICdBKo540qCoN5xw69LDGwMRol0S8Td3Fo29yoY6Lw4N70xUbirypKJzKn1849XLj1PE75V3yC6758RAEjuKuzFAZjvdklQnC5v9kEMgLlGzU8aWOiZDmZbGjRVlL+gEigvM2CYFjSu5Nbab8Q6awA2czd2LgcEQIueRwAZCRYd1KGTJn9Cl/a3D6MpR91HjFiJFsRBnBUs2ucWHKnwRebgvkWpf+UGXrHKztJINtFMpwuXQMxQ7D2hsyL5uze2bvvMefIkfo2hZd1+Lg3q9lbRi9bUYvoGihh3aQQlXpmPjOeReC80e6xuikE4bCqXRv4RReEKe0rlDXwilCiw5tdKPdLE5dw6J8kpJ8+hSSxkVp9lMlHvfGxiIpRUxQPnDjZ2JwXVLsHEk32KULSlEcWRXWFiMjMRnGZP5dP6jp1mxaS5ROLOMQfpmXHQaKYwx4+ja7hjNuZD7dzPAZMDeG+QHQWgHw/mB/4l9o3yA8kVIfxYd5UkXXKgAOAxoIl5ExnIEQfwv14LBzwZdBoU3hFZT1OgFECs5ZXPnYX8fvnTMx+oaUAjh7KQYZCu7cnFipaIBZrLSmxu4/ejOI5GiErm2xWi7ii1HlBZwYFE4VToW6Xj+nFvM5FvM5bgSn6mYCIkK7ap8Xp66iUNKIxKOM/df5jtoNhsPGYsK14VSxMIUcR9HnN6bFraFmJd84kD9sKF6f303DOmVWAY+/9FKxRsTwXfA3xu8GJkS8zm/R8p+HtZFrXdzlGq/JzoM+DkOXBGHtjuzltKm09eHhwS8EIOdt8qNmfmnK7x1cPK5o/FL8xzZafoO0EZyXM7Te1urLw1FzzsIYBdMbTzIXSR9dHWttvtkonCqcOvmcIhg5Xvt5cuqqM5S4wMRB6MJ/KloWGAmz/N83KghFGDiOIhSnwOQPill/dlaLbEocp2oxuiGf9mcgH3ESrYVxN3N2Eycri4bLloAsniYRWbeiKCfAeIodrALOxC2wa3ROc5yFZlZjaJycAZ0eGqwhMYKSxOT1TNwOBONhPYC4Qzq0Kt8oJYSg0djmTUvjEIc4941nD4qOE1L+7HOA4RAWKqOlOug4XvPth4L7vkffG6w+/KXUdwCUVj5tSJKbk4TCKUHhVN72vGkngFNYpb7DtXPqKskhpWMldXFuwYy0dW6F5BLmxcd7acf6N/kpCemK+B1FrcvIhAWSqkBRWDCUCzivU/YQNyCNRJ6Q9KkvN9Z6UC8AMctmjjCFdzFGn/wxyBmxhsbEuDukpYkFkqI8Fh5r4f8v1lbevEiXTCBjP2SSHfo0HI2TFbuG/OUUBJXBg7FN03+KN2Vc9MKGNC6byo8PUACGC4hCxOFLZfA7JZeBAsWzJtb83wjW/omL8SqcKpx6WXPq+PNQgrBHgfZWhoxHrFBqXR5qlqoTNHJsB2Xill0cOnytQSMBJlJDcaVQcPZVdu5EHMhY3uBGSCflC4+Z9ISpNJEf7LS7OZkl/rfYJ+n28D/GuIZZT0Uy+mlweHz0544GedBeQnbL+Gu5RSFVZmTWse+rTbUb/D0ej4yIazdR3pPD31P/5k8I7QqpUTn5fZHJYNYHeQmDncLwcff+TTOUxZuPwikUTsU+e/lx6thtxHn6gyDYeSWSfeMb7OsY5MEngPHXULS0osVFeWcgsyYCBdL0itllZV0FPOz0MO1Li3HrA82xw59H2aNxj8XT8Ab27Qgx/smjwUmQoqSG7/PnDUrK2rLeilStMPihAB5cOfx7/Nv427xuvk6c6s6Dvs2HMdWVORvT2L5hTYa38eCZuaF51TE6wSicukrZhVMvaU5dW5SXH5w8ZnwcP57ENnym0e0jH2CQH79ZB5DzqHPrLKa/9v84MLSfBwsZKHUK5TXIns/hNx79lCfoO1rrxu8Hg5Gu5pHAhjHNvAkA5QniSOoOxmDhkGWyqiiVF+wogsxaGQrMLtsMN/LPRhPKL6QhkDKl0IidPyAbDdoyknOkl1F6cUUL1b/paNyBnO5Nz8hIjUSKEPXD8ZhZTrcAPhLIJTkE+Q4ZE1v6Q/tYfwZjkEH9xKBwKtSncOrlxamrb2wMQr/WIbn2y0c7NXqtP7xFIedbi69U8XCS5JzfTITsub4OSsvef8cuGHixFuw4jv1ALedt2dA+eahMrYfWo1wQBweIbcwtgY0vgREP2S/8hTYFH7MMPgYvBc4IT0AmQCkza+aBzaaxQqa8NiL4PDy+M7QjPMY55M3j+HgG/AsGSP3AlI2r7wcCZTus/b1EAxcJ54ufg8pw6q/4Ehq6U0DeT8+hc9m7aOBfhCkKJbfEhuQ7GSicKpx6OXPqeWbOSw0cYGBlxfrmdT8SaZMQR22aNzysV8bdm7EaBOmkYB+M89WsNzrT08OaZaNJGH0FIEyvh1P8rO5ZqYPyRySItlNmalFoibd0UvESLDksYmRlhL7K7hm6IOR6yWfkI3kob1sgDWcP4awfKJUZys0uXxesZCGF2wm0flloez6msW+y+3y/EELdMzkLP66Vyhtl8OSicKpw6uXDqWtaQ0md7HfPeosgdC+NJSY+3A9ubDzFjVN+rIPKh2wsckhnLFMsfBwuR0la/P3BuuKNLQ4CFm6IC3MKcTNVLD78mQ9YJlhxcAMhaTR4WfkjSZMrMquASJ6fbybzVMsqL4Me/cKxiV4KOQhMTpMkzARAaw3tCbARkXic2u3rhiz8VH73oYOjDhr7eCOBCKncINhE0cJbJ0Bqdxon77oJY5ULt/+bM+GIRCFgbO3ebBROIfuhcOrlxik6iXH6BQUFBQUvPZzcwyIKCgoKCl5SKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArKAqloKCgoGArqI778WP3/gw758Ds4NhiOpmCHeAccP65H8OpM6dQ1zWMMZjPF5hMGuxMJ/i5NwD/4+NAVWkoRSAGGAAB0IoAAETXX2n2//6v/S/DWot/pT6Auq5A11koM9B1Lf43+0v46eX7sTPbwc7OzvVX8DqeDwAMhrUOzOy/YzjLcMxgZswXK9R1haqucOXyPpRiKKWglcbu7g4ef/1voOs63PH0D6Gua1RaQWuFf32Hwv/wiEGlNYjoBfX9jYBzDGMM7rtjB3sHCxjLcEzI7R3O/g+Wvso/h/7i8Ldz8bv3v/2tJ6bFx3HqlltuwZ0Xfngjp5arDtNpc8M59cSTF2CtxWtvv20rnHry6Sdx+tTpE8+pvW+813MKUIqgVYU7nv4hLFctuq7H7u5swKm261FXunBqhGMViun7waOtsSDS0LoGKSUPYgcixEEjIigCCAwwg0CwzKBYEuEF931oN0sXiNC/kFIZxlg8d/kyDsw+tFKYzUT4XyxBYc8AAnnhF2XhXA/H7AXXt9k5KCI4a+GcAzQQXlKBSCIIDOc4lv3CO367CIJqjEHbdpgvCJ1hkREaTp7lBUoIg0+gRIBQ3lr5Fs6aG9j9GN6+AAAgAElEQVSC54/jOUXHcMrz5kZzCtvnFJhfApxiKFJwtodzADR5TmX8KZy6KqeOdXlFYVYKihTqZoLZzgy7p2a4cM9H0fc9+t5AKYV/++YpfumeCZxz+JnHHH7pTVP8X+cncI7xzJ0fhrEOjsfVu354sQdB6vdCQURo9BS/vPtR/PLpj2K9K28c/s1dNX7hrgrGWvnPWJjeQCsFIuUHGmDH8rIBMJtO0HUt2raF1hUAgnMMaw0YwM/fqfHzd2pYa/G97teljV765aX1ojVvI8LzjTH4yutqfPH2GosVA9Ag0n5kh2xd5+7oG86/Z3TtApefe2rbVX9BOI5TDhhwSmkFghgLTVN5OSdvfdqXBqfUDP2yR9/2eDE55ZyDte6aOQUwZtMGbdehXbXQWuPiPb/ly7FgAL0x6I2BtTY25SRy6rHzZ28ap46dofRdj1OnT6NuGnRti65bwpgWVdXgzOmzUEQAA31v8P34IGqu8exdDW574Lvx419bgAB0RDDGgiBWyrYUunMcten1TssTCJPJBP/L7j+HMQbVQqOb9Gia5oVX9BrwUw91cMwwTuyF8MIBGFoTGIS+NzDWwDrg2XMfwuu+/n50nYFjB3fK4Rfu0vjHrbysVssWP/5Vi6rS4LqC6S2sdaj0tvrrhcM5i67r8cXX1OgXBtYpkFq3igPxBy+jaFQNGUxEYHbo2jkuPP049veu4GD/CoDvupFNeV64Gqcun/8YtNa47aH3QkFeEsEidmFWQgRnHepab59TzABtj1Pnzt0hnKo0uu7F4xQRgRRgjTuWU8+c+xCIAL1SmDRTdF0PdgzHDtYaXLrno1Lvx34AdV0BFaCVQt9baK1OHKceufsMLl68jL7nm8KpYxVKM5l6H6RYF6bvQSSuLiLAOguGTCOrSvtpuoV1DgoUp+pKERSp2Onb6Ps4naUXPuskEr/pbDb19bfo+h7OWdRNA630DZ2mExEURFCF0N5d6ImtiKC1EvcWGNZZIb0iKFYydff9TV6BN3Xl3SQU/cXsB46i910Q/c2D6b1AeYHcVvuZZVbSdh0Wyw5dp+GY/NT7Wh6SpuhD68mh71Zo2wWuXL6IK89dwnIxR9e226n4lnCtnHLOeU4RjLUAMOKUunGcwt8+ToFEkSpSYMXXwCl3Ijl1MF+i69xN49SxCmX31GmsVgfoug51VcMYC8ABLL62p+/4DRCJJfKaR94H5xgX7vowrHMAFLQiPHf+Y3jNw++T6fsWJSgNEm2lXCKCrjR0pbFqW7TLJRaux9nTZ6En+gWXf/yzAYBQVRq9sYAXwvSyIDR1hQt3fQTMDpWrwAxcedO9AAGv2/8J/LOHejz1RumLC+c+jLsu/FNorbxffrgoybRu1Ypv2EW/cYDWGlorMG9h4ZflOau2xXzZ4mtv2AVY3DhElNlGGQHTMG+0oMJFzhnM53vYu3IJTz3+GEzf+5f0yQpkvBqn+r6LVmFdV3FxlZRC4BT5l+EN4xT97eFUWHsUnjC01gABdV3HftjMKT5RnHrorlOYL1c4OFgCJC7wm8GpYxUKuMP88BDtqsWZs7dA60a0u1Y4OLiMvrPQqsIrXnErnBUXxny+gL3jN/Gax94HhsOqbQHwVmYSOcSyuBELfOwtE41/0/wa/mX3ATTN5EWb0v7iXRX6Hvge82u4++KPoKp09Aff/sj7sOpWePbcbwIAur6TqBQtsxRFBHYOWocXAsNai77vPZnSov74pREst64z0fVxcHCAs2dPYzqdoKqOF5VrgTE9vnQ7YbGsYbkBoL1QHN+3mf0kCO89RTCmx2p1gMcffQAHe3tYLZcAhwXIdevwpuMaOaVe/5t43RPfj67r0XY9ptMpqNZgOPRtj93Z7MZxaotlChKnDvb2MJvsvKiciuspxiIomfBdpSusuiW6RYvdnVMZpwiVruQlupFTHaaT+uRw6tI+LBNA9U3l1LEteu7SswATprMplGKY3oj/lhTOfOV70EwmaCZTnDo4jUW7gjEWzjq/oPUxmeYuOglzJIBp2JDrFydvbSjvu9yiXIoGFuvlX/KPYjqdvKghgT/1kCzKPnMnZW49qUDTNFgu51jMF3DW4DWPfh9AhO62DqqZRKup7w2YHawlPHPnh0E98It315g0Ff67+xaYeD+2lC8jIgv6Mn4g4JfOT3D58gr/6qKLZEgLytfeIcGCe/DOXSyWKxzsHQCqAaKVkxEw3DMY0LGNRQAxmC0O9q7g8OAKrjx3EQf7e7Cm97/ni6UnS6Ecx6luBTTNBJPpBHVT4euv+w8wxuLW+78HWmswAGMsurbF6d2dG8MpurGcevWrX/Wic0rFmQY2cKrGInDqll7cjAC6rgc1aiOnjLFi/TuGsRbW2mviFBHBWgljfqGceuIbb8VquTpxnDpWocwPDzCd7aKpKzDbzHWi4ByglPZTREbf9wCn6ZxxDtZYGJNCzPJ6DEhwHcJlnQPU9mco7Bc+tdKYzaY3wlw7Ht7tyRhO0ZkZdSVugr7r0XYtlBbh7zuDpq792Ei/M4swd103KMNZEXSlZDzCv8wSORTay5DxJZILjI9syafqY+RkFfLCk7HHYtViserQ94x6okB5PPzIXFqznrLvHTs4Z7FaHuLK5QvY37uMvecuwVor0Tv+we6IMm42juOUJi37io7klPWcsrG8rXMK2xf5k8MpbOBUBeLAqQ7aR9L1XX8Mp/rUv+7aOQXeHqe67mRy6vh9KEYWZZgtrG6AuBjlsP+We7EPgJTC65/4QVy6+7cxm81wdnYaUIDtelhrcfsjPwB7m/Nx0Iz/854JfurBDorEcrgeMANtb2DJAti+L5bhB4RuhEstew6P/+Y4fb7l/vfA7lroSizTZ+78EG578L2odAViwuXLVzCZNNCqQrvqsLszjfeLQIvwL5cL7Mxm+OmHekwmhE4pGNNH37DW8hJjBv71Gwk/+/UKzjr8xH0rENWYzsTyms8XaOoaRDWU9yGnvQriSw77Jupa1ngcOxhj8IVXK7SHK1gHNJPZRksqJ10SW85+JkABpm0xP9zDY4/cj4MrV2R9gVKMffJtZ4EIJwjHcWp3dxfGdJjPDaztANaYzWYwf/f3cFkBO19+J6y1qHQtfe05FWzHrXDKWkC/PDnlnMwmAqessagqH1DEhMvPeU5p7Tk1G3Dq4t0fgXMOky+8AzuzmWyArDSs4yM51bY9JpMGzjr01uL06V1Mpy+MU4+eP4uLly6j7fnEcepYheKsQbtyML3BdMoSvaU0qqrOZh6ER2//Nbxy9kowW+ztX4FzwG0PfS8UKVz+ht/C2Wd/GIolguK/f6CFyxr9PGZ6A4TY8G37YWWzJK9L5g1Eipl3ePqO30Tfdzj7tXejqyv8+zedARHhA1/5XixXKyilsXNqF4+4X8XfWfwkJpMJTC/x9ovFHPsHh2jqGvfd8u9EYHrCay/+AKodEXKlgP/jNQ5KEX726wAgIagMcakRyXrLL5zTeE/3K/jM2Z8EEWFvD/gXTxo88YbfALPDXc/+CJQaLgqHhVBA1ncWyxX+5vVTmA4AtIz1cd06/s27SkJU1LPPPI4rly5if+8yVsvlwNoMBAzFiNDzhkJvLq6VU8ZYvPKVQ05dfv0HoUjh9kffh964yCmthy6NF8QpTq6NbeFmc0r29vQwpkdXV5ioibwsibBadZFT+/uHOHVqlnHKDDh16bnnQCDcZgyapvZZC4RTh/MlFClMJt5IiJyqfZCFBFf0fYeqlr0wy0UH7BBWbQdmhzOnTx3LqUfuOY3FcoW9Zy/BWIWTyKljFQqD4BcqYEwP6xhNLcIvIY4OAKGiCsvlHPDBc/Abh5TWqLybxloHCweiyrdKFpOvd/7LLiz0bd/cuVHlHgelCBoqWipd16NvDKyThcOq1uj2Oh9OWkGRhI1WWkGTRKtYH1HSdivs6B2JuyesCYi1FtYCXe9SCCPghRkw1qJrXbSciWS/Q9916LveC1daxAXJ/WFa3nUdDhZLrNoexkyjDEXZHy0aDjkRvboAAV3fomuXONi/jEvPPI35/ACr5RLOOWTNGi0wcv7PicIL4ZT2i/dhMfeGcGpLEV5j3ExOOavQZZyq6xq6UsKpbhOntOcUb+SUGvSR55SxsORACgNOaS1WvvGuMmYn/awYWiv0XS9RYL6cYzk1D5zCieXUVaK8JKeNUgq97cAOQEOo60Z8ks6BSAR8f/8Add1gOp1B6wpX3nwvqqrCvfUP46fZ4NlzHwEz8IYnfkA0nSKwkvlvWMe6VnFjyCYvEF33FP9IxGn5jRf+8IiwK1kp4DWPvg8HB3M8/MZfwfTCD+MnvrZC09RQVYWn3vhBOOdQk8ZkMoFaKSilUTc1lm3r3R6EdrXC2dNnUNcVrLX4xXsa/E9P+JQRTv51zqFtO9SVhBgqIvzUQx0AeVF94K8PcfhWwk/e36LSGj/3hgpPvfH/wa1ffa8sEN8qi4t5W8T3T5gvV/jq62cwdgaC5IOikYivIZuWx8k5OyyXB9i/8hyefvIxHO7t+2dlhGa/v9vLg3cyI1hSJ83l9UI4pbUW46LSfuOdtK/SanucwsuPU+wcwLIBW3a6M7QG6qqKCqWuPKeUkn11TYNVu9rIKen/LA2LYziW2SezHXBKVxXAwpW27TCZ6LimVFUay+US7NfJmI/m1P137mB/fwFjAaKTy6njZyjcg1FBtlQpKF2hbiaoJzUOD/Yk/42qQKSws3Mak0mDuq5hncOkqcFgvHP+7/DArYxqUaGuaiyXLXZmEjJojIVqUvy258DVwYCxok1pCykihm3GTfOSEAEX7v4IDg/m4H3gwrkP4/SlD4CI8NQdH8Jr/vT7UVUa+2/5OKqqwayboa50XPjWSmE6bdCuVn5RvcJrvv5+mB2H+UKS2c1mUzQNMJ/PcfnyHrrO4v/+hh3UVYV/8WQfLaKmaXDH0/8UDg7L3uDH/sbg0ds7PHvuQ2gmDerHvl/2SVjGatXj2XMfxCsffi+YCA+cOwvl9IYZkhfOI0eZJMbfGrTdEk8+/hAuPvsMVosFrLXilwaigG8apkScfJ/AycE2ODVfzCXktapRVxWWzFvm1LZdXripnAqBD2DAWRejQ/veoN6pUFUV6qYWTs1m4lU5hlPT2Q5M7zDnVeJUXWM+77G/f4ius6h0hbquMPPjEji1uzuFc8KpvjdYrTpUlYauFA4O55FTD507DWt6kAaYGIvnDqFUfeI5daxC6doWVT1BVRHAFDV43/ew1oCgoHWFM2fPoqoayMasHo4trO29FdzjdY//IP79285gUk/wM7UPueM81YNkTx30z0go1hrpHH7k4rsxnTTAK49rxfPDzXgRZYYBXvPo+zCfL3Fqf47HXvurODyYY3fX4fZHvhdPumfheou2XaWss34KPj88xN7+Prq+g3XW5/SSjVo/+UCLC+c/Bq0lgCLkIvq3b9rBqd2pt0glR1SYzte17GQ2xvkwR/H1gwjWWvzvr+7xPz8rCfWeO/8RHNgfw8HdBCiCZh191LnwC6eTtz+3r0IfHB5ewcH+ZexfeQ6XL11A17YyFQ9j4wvKraRc4MO/YQxP2gxlG5yiw7ncR7Knoqn11jhFFFw228PN5lRVVWiaGk3dYG9vH1pr7O46NE0jLq2+hWMbOSXbHBTmh3MsV8uNnLKW4ayDgcx8wsxCK58Ox1fgapx6+q2v9ov7hL4zOH1mVzIgdD066wDrOaXqlwSnjl+Ud+xTFjOcA3QlGlJiqyUnjq4qzKY7UJVG17XoeoPexy4Hn2DwTQafYPQTDqo/FOIQE3+U5nWOxae87UV5n8fnxXwRhZkpAyBS0JVG5XfxrlYttFaYTCYgyD6EtmuxM90FIL1TaY3VqsVyuZRQU4jPVqJTFJw14s6wzisT+b6uJBU+QXlLjgEKexEQXSBhOqyUBiBltG0HY2RKLn5myJ4IpyScOYxdHMOj+1Pky6LrVti7fBF7Vy5h/8pzWC4WyMc/LgzmllQQ+PiEIPT5IuLJwTY4xYFTKo1N4dTomf5/a5ya84hTBGMMrLORU4DI9Wq5wnJ1HKeQOAWGUoS6qlFVVRyXq3LKbxa01qHrOhgzeUlz6liFonQlSQtN7/2OGoCCNQ7GMqq6Rl03qCcVZrMZDg8tlos5lvMlJpMJ6rrGbDrF4dt+F98HgHqgNz+IZ+/6IOpK444n/0kU3qEMcxSIo2T7V279bfz4le/BtlNrWL9R6UU1bL3gW+skTxeAvbf+Dm7pb8Ezs99EVWm8bfHP0Ewa9PMOy8UKp3fPxJQOdVPjidf9OrpVD+MMrOlhehuVORHh1vu/GwDQTyx+6mEHZxnMFXZ3NX7hnPjkGbIAH1xoz53/GN7w5PsBKPzc6xnvmoeknA7fh/+AtvshEBks2hZotMTYe+ssboKKjRQC5H50hiwid+0K8/k+nnriUVx89mlYYwBmSI4rjgKf3ycfknWVvh+lxDhhCmUbnNrd3UUzmQKQ7MREBOtkPWx3Nr1uToXF6Zcrp6pJhVfc+gqsFkvM5wt03/IZNM/V6OctVosu45RC09RYrdqNnLp8/rdw5qvvhrMOFozeiOuoqRvUVY3dnRmMP1pizCkiyF4cKDx45y5ovhTu+ZxibdeBSKHrLaDqlxynrhI23GO16FHXDV75qtdi59RMrNNVj53ZLma7p1A3Exwc7KNtV9jf38f+3h5q3SDsg7CrFZrJJB5E89QbfgOvf/j9aJoKenK03++4WbcYBjdoeu6f/2KmgJJkgCKYj9z+q2i7Dv2BbLJyRHAgLBYr2WgEQqU06qaCMQbM7HdWT9A0DZQCLl+5gvOXfhRnzRlMd6fYP7CwTgSqrqdodmYAC9l+/pzCj37lAH3f46E7P4idnR0orfFR+if42cd/CM/c9SH0fY//9kvvxBOvX0lcvHNwDDx6/lYoXYHxz6FIxjdEngTkvvz4HRFAYqlfuPAULj7zFA72rmA5n3srWvkFaoscuaDnf0cB5022041fCH4+2Aannnj9r+Ouix/wnFLo2g7TyQRNVcXDttbxt5dTB4dz4ZRfE7lw/mOotMYrFqdhrRtwarVcgZkxndo1Tt3yirM4c/YsptMJlFZHcqo3vUSU+VDlnZ0ZlNbY2dnBZFL78OEWqyWh7zuZnfqF/d6IQiDtU86/xDh1/MZGayT8V4n/sF1JaJkxPZp6JonSCGjbTmK+e7m+rhtMphNUVS3+P+0b47VpXftw4qxePPogfsGjw1SYfe6cG+HvBWN7ScGv5aHyjyJxX6FpUGuNrjdgNnDOwliDFC6DmHRO3B2M6WQC5ywcWxBkH0hv+v+fvTcLkiw77/t+Z7lLLlW9zY4ZYAYDgKRokmHZD1602aEwQxRFAAQBgjuJZQgyLMkR1oPDb37yg16koCiSEEhogUCQAAmJIimZDjpCYUXIixQh2yIJzEzP3tNLddeamXc5mx++c29m9VI9GHY3WsM+5KCrMrMy8557/ud8y//7f9RUkETiI6bIfIjtZnlupcqR++6c1EGsFVY9fe/w3jPJX9UagyoKfASvLSiTY8TXFVZt0ipBFm2+nSE42nbFcnHE1Z2LHB0c0LWNfB+tOQafTXd8c2Ufs6DICz9tPgXX/819MO4cpiSfJZjizmAqvlMxZaFkA1MpY2rYXG/EVIjxppjy3qFuiyk1YmqoLdpULe57P+qKQcIYiy0UIYL6DxxTJ/dDcQ5rxUXv+jZLa8soiwqlZKG43hOcJ8VEWVSUVcWknmDLAqUNinUM9aGXP4zdMiNNbqj03fySQ6JIqeGirh9ifai7Ee8dZu4uUxxvSJIiUttPvvGxcbEcHC157bEv4MKG3EY+mF0GBiR+6ZmC7/tXH+eNJ38V1/coBW888assTp/mA/ufIKbEpff8BjEGzi2fkw3MSUe3586DM3qs7H34lQ9jtCG9N/Hmk1+WupOY2H//76AaJW1Qy4ojfmqUqZD/H9zx6+L2x/5NxBRomgUH+7tcvXKRvatXx0V7A2PvFnHd4d/h+o8lE4/9/Nbvx70adwpTWg9tCSIqt4/4Y2MqvTMxNalKEuWIqRRTxpQfX7jGlCilp5iY1DVN14yYahoJO06nE0wS7yfGMOawBkxVdYkeMZXkZyXaX51zvPrsNikmjJICR1sU2LKkd0l4zv8BY+otHCilxH1joOtCPsUThS0oypISUeZcZebJbD6TRK9RYoE1K1KUyTG5KCtBXrwQE/y99xWQ4NMvdkJxyxeRNib1+hldu+d3mjYsaLvjXPybfRaMRAWxaiTc4LMy6vaWtExt247DwwN2nv6ncs3KcLRYcMZoyrLkM684dqdV1uNp2d7eZlJNURhWq4bgPb83/ymstXxno/j5dytiLPj0i5HFYjkWb5VVQVWU+BD53u6LnHnpg1x5z1fQRvPPJz/On2s/S1M+h60qkotj7PZYovcmC25Qae27lsuXXufSG6/TNs1argJ1sz8bOJ83PpeOQ+rmk7vZ3PT+GXcKU4tH/jEPnf8Qxmhm8/kNmFJDrDvx1jEV/mRhShGJUR3D1Gw6kTCXUdTTmmWzuAmmWoz3zGdTrC0wWpqHxZSwhT2GqaIsR0z1vctOiRwyk0nNqm2JyhC1Jen/8DF1coOtsmI6nVJWNV3nKIpC3HUlF1SWFbYoaVZLcRlTxAdH77osMVDw+Os/yNX3/tNsQdmx4c3gWmoFn3peGrYMgmZDwZBWakNNNa1Xy3hxd6EIazSm7oF7nhK/+GzJZ15y+dfELz4jt+S58yKBUpUFfdfxxuNfolYChhAiTduKx6uULOYYhZXSrHjq3U9iTAEkLrzrSxS24LmXvh+lPI1W/BX3VQBi/BC77/utkY2HF20ipTSPvPr9XHrmyzx8/vvRxhC/TcGpv4YdKnTVYDcdn6dxwan17+1qwd7+VY4O9ti7tkPXiGV+6znevNHXUSGBlEFxszHYdIn77zCBO4OpsqxJCepJLcKRN8FUOjZhf7IwFVkfXilJtbuCLMiZeOL1j3K0WHDlPV+mro9japrFK90JmGrbhtNGkuUxyd/FrHAwHGZGGxQa7/2IKW8jrz67JRVIRhNRVNM5vIMwdeKBYnLVqIidWcmF5HhoUZRoIwVAfd9JolYrnFM5GRUoQyRmlU7IVaskgvfEXD+RstwHQIqD8mYO8wEqpXyxOQachoWytkLu5LhdnPlOjk3V081/RWBOE5PMs7WWtm2oalmyKSXats3WpBmpjJKIjMxmU5qmJwTJv5RFBcih0feetu2y1ebHPuVam6wgrSHFdWJWG1CamMAUZb43WaJh2JnWod0xpjvcZ+c69vZ22Nvd4ehgn9VikS+e0VoaR7ouKnJ9TPfGGWQICKTN16fNZ++vcScwZXWRQyNifd85TN0d6ZV7jalNAcOhKl1pyWsIpgqssTjnb4KpjIXbYGrIbwyYkjotLY3PcjM0rQcV4usxpUFJp9J3GqZuU4fi6bqWoqh44smnWS4WufgqMdvaApXoupbl0QKtIcZqPNWLsiA4x0sP/QPsoqCqSkJZcvGpX+eh8x9EKcX+B36b37I/zGdeFjqdc4GqKsZCoHWBVhonJ+XQcNrov34nR/7Im4cF7uAY7vtnXhJXWQrSIj/zihqZHVopnnzz4xwcHvHvp7+YF53m7Isf5Mqpv4cuDWVZ4rxnOp0wKSd0XYsxBfv7V0gp8vSVH2X57f8rV5/5J/jgpbnTnlTn+nf9Gu9+9Uf4lQ9MScBPvrxEnVq7ytZa3vy2h0lK899owxBIIWUQblhMkD1Mcl1EcKxWh1y9cpGLb7wmxXkhrGO6abB5ji/cEU3jfY7jRnds/jZ+Puas3ySOfj+NO4Ep7zy2KHjj8X9MWZY89vpHcQyGiKGwdtRl+4YwlXhHYErnnMaAqaEuBOS5yWSSa3viiKmUJEeitWDKe890WjOZ3IiprS0JMZL7oSyXS7q2w1rLdDphNpthjKgDD8n5TUyFpAloQsz35B2EqRMPFGsLtra2OXX6NFVtcN6SogaVONjfoW1bYpCTuescbdtgbcHZc49wdLhPE1fU9YTTZ86SEqI91Pdce/afYq3lidd/gJ9RPrNKFGUpxTsJkYp+5JXvF+stL8YQpFVnzBad0ncngZjUPXLP85CNYGB1DA6mzFdZiRxEaWuuXL7KfD7lnBULV2lxlZNS/NxTij+3o6mqmpA9D2MKmu/4fc4+/70sFkti29A9/VWUNhS24LHXP4aq4FMvNMSUcHGjdw2wKj6dWSd6baEoQGsSQhJQ4zXIBhZDYH9/l0sXXuPo8IDVarkOpWgzgudmC3U9H3K/h/4LAzgEOEnag3PjG9yPHsn1425g6uJTX+aJ1z+KMYaqLMZ7cT2mJOFsbo2p3Ar3TyKmZvPpBqY0SSna3qH0jZiaTre4+t7fYLFY0rYN6VTi4Zc/QlFIDkxpSDFkQ/E4ph792gEX/9Qj71hMnXigFKVIP3Rdy97uNZqmAeTUbZoV3jnILmRR1gwnade1kORitZYKVWMt2hiKQqpAVQg5CbjuWGZtQYxhvIIUE2iRkAib/Ok0WFN3wT1PKV/HHX3bm471Z+TbNsYp8qMaCmuYTSoePnuW/o2OruvZ29/DTx09jt77Y1XSMUUODg4orMVYg3eOqzs78pZaY+uJzHdRkJTGhwRpqNyO9E4K7kIEtJHQyMZcqKTEIR4fHiq1pQBvuTzk6s5lDvZ26buOFMTVPylGe92sHP9nSFLe6uUZHTdd+Pfh6XL3MWVujSn1AFO3wlTvOpG3dw7n3dhsDG6OqWvXrhKRTd/WJaaq0PatYEq/ozF1cg7FFsQgF3W0OBT6nDZYa+nbHrJFkxLMt85AdjW7rsMYS5ETiI+99jH2P/DP0EZTlSXL1UpkAZxUhR584J9hjOXJCx/De7mR585/kEhEJ50tiygFP8NVJYZj9w4PmbF7a02BhJM2HgOMUmAVRlf8qV1AcuYAACAASURBVKNPcLj1c1y7tsPOlR3cIw6XBAAyJDHrvePw8Ijt7S2ssfR9x6unP890a850vkXa+qukFElG84vPtjx3vpXFnzWgmq4nJcVrHzjH2K2N9UJPaoi5r+cnpUTXrtjb3WH32hV2Ll+SvI5SGGPlNg201Rw2G1lI3LhwVf4/cpjmuCt+s2V+0iq/v06VO4WpopBGUAOmpDguyFxnCXaFwWg1YkorSSLfElPwJwpTjzxyjsODJdeu7XBwtMdkUuFcT+82u8zeHFO713ZHTBX1lMvf+TjGaN794gExhJtiykeFsus2s+9ETJ14oDTNknL7DEVR0S9XojukFBrFZFLT9yJ3XlUVIfQYKwJsk8mMelJTlBatLYeP/zbJS6ObojB0nejjfP3U55jPtvg9PkFd1DwXe9quE7ZLbr+pN5JfRWHzz4lBl+iOu+f533vduwFu7V5KMajluw6f4w9e+0P+9am/yfvrZ1i973eJkynLVcOP/+Ff5o9mK/q2Zevxx0gxEnAYY3niiSfxWz9D0oqDgwOsLdDG8Oe15evvmW+42PKTtQWl0pi0tlbXdFMFWiRdUIm+a9jf3eHll16gXS1xrmdd4Xs9/fTmFtUxjSe1/neI5w+u+CjYrYAoL0qsRQePvc9bstzu/bhTmCpKS/BhxNSbT34ptwxOvOfSj7I1n2MLi4/xAaZu9rhSPP7aR2if/CIHh9e4dvUa73//M0zKEqsUy5VQcNvm1pgydUXSisurj2BDizaG59+z1tgbPgcypoqKp54/5F1f2wXgwreee8dh6sQDRaFygY7CR0fo3Zj083kxS8XudGQaFaVFW0VMHu8jxgQODxaSQIrSEna5WAJQFiVlUfDT53tsEelzAd8g93zp3V/ht+wPY63lv31N3PihD4EaYrJ3eJHGmEj6m7MZjYmwlPil95Z86sV2FKQzWvP5b5vxdbXNd7045fTpU1RVNbKEjg4PYAbT2YwETCcTjLUoFG31HHvXrnJwsM9icURR5up4pAnaqBWkpSJ7a+s05elqtPJQiHKtkq7VCY33HdeuXhHa4u4OzXK5wX4Z7CaGFQyAUmlM/B6zrHKyeLTb1AaP/rpFvI4XH1c+vUF4MMef73Yi+Bsd9wpTSqlRQ2sTU855kVbPCrzHMMU7G1PDdW5iyhaWuqqYTW/E1GHuFXIzTCVtuXD4fRlTL79lTF38tnO86+t7GVbqHYepk/uhxEgMAa+9iNl5L1/cmCxBQFYRHlgV4nb3XYP36+b2fe4vP4y+dyIxUhT44EXSIErjmxQjSYFzka7t8LXHaDMWW23KYG/M6x0f99qaGq4pxijJvJTwuSlPTInSGoypKApLWZbM53OMHXp/y1yF4NeS5lWJUhofIs2q4fBwn/29a3RtS1lWIzPEWjsufpSiqmommZu/Dn+s47sheFzfsr93jb1rVzg63GdxeECMaf3ajXHD4svZPzW4+qjRQBj+WuXPXoPkNg74+KR8yUG2YthE76dxP2CKqsaO9NY/OZhKSQqij2NK3xJTfXdrTK3a1R3AlHrHYerkSnnvhUrX9/S5dmG4oJSgricUZSGL1Ut7S+d6+k4KsER+Xah41lissXRdR1EU6LpGKTjY32N19vNZh8jwxIUfhJi4+NRXmP1/380ntpZMp4k4qSV5NXLMh1igOs6W+GOOLz70OxSF5TPtx/74b3abcaMHmeh6qXT91AstvQ+smkbi43XFZ16qOP+K598Uhq35FlrpXJGbuPzu3xhrU2azGUVZ4nxgN/wwr7z6NRaHh/RdmyXoyatJodAQIZJIUTa6GKI8vrFwZTOIrJaH7O5e4eUXn899FUSTaGASXX89t/r1+tj2sVdmI3ktAZ5jwGr96sESk+8GoPPCFwbcEGe+zxyUe4Kpl879fam1sIZzL32Eqq4gJqlBWjVYY0hlQUzxOKbU3cEUwxXegwPlJExprfEbmNr59n/OKb099pS5HlPe+Ztiatm2PH/hv2JxuPO2MPXmt57bmI93FqZOPFC25ltMZjO0yT0zkElyIZDi8J/QEJtmJa0zrUUrk5ONmrqeMs/vAbBcLKhmNQrF/v4+RmumsxkxweJoj+bs54W+12r69/8Wv779aeq65jOveKl0jREfA+so4HoC78y4l7tQ4u8WX+QnDz4krJ6ixDlRKQ0xsPu+f8bhwSHO9RSF5QP7n6B3DlVJRTt5gdS1eC4+FCgtIYZLy49wcHjEzs6LHOzuklIctYWstRhbYEwhVtdGQ6CiKKmqWizloRgsBlbLQ1575UX2d6+xODogeEkeKyV0x3SrO6HWM3r9gpcZ2LSZjk1NfmF+PvMwGA0KhOKKLHJthraokIgE3xO8z6Ka98+415h64fTnmEyFEvvwyx+WFrdZ+du5e4Ope3uuJ/YPDiiL4qaYUkrTLJc45zjY28foPK/cHlN7+wccHB6ys7PDwd63PsDUTcbJORSls9sVUCYv/xhJSouLl+O0iT6fYhaTF3kIITcCCrSdxpoClSuEcxUJWmnqepJPeKkUHmQkQt/z5Js/xHPznrIEjxI595SkqFExWlZv1fI5lqe6xZ8M4mj3yjv/8b3v4wsP/w7GGD65+IgUHHoRBnzo/Ac57T3BBy6958tceOLXuBjfIFwOeO+kVwIKa4wkcxXYouAg/Rh7+3scHBxwdHggtOLsthprqOoaYyuUNnSuHYuvSKCNkaWoxXpZLQ9YLhbsXrvC3tUrmdrq85zLJI0SHvm3cVzHJoHjINgUvVPHflDjA4OrPjyUhs+L66Ix+e6RGNYhopj7URyjxt4H45uJqUtPfZkn3/yhMW8SfbgOU+quYSqd8PydHtYYUkwEHygKjmGqKEum0ynBBxa5iVbfS0fGkzDV9o69/f0HmLoNpk5usKVVlm+OuTgpjS6QLe34uHc+yxmI4mmMYeRgRxJtEzG2wJoiu+2SJLRWmgXJl4xjQsx5L81o9MBGEUVNGy0hRnwI44ESUxovIh27AcdjfesJTzfGIDf+doi13hubSrSbYF0TUFiLN54+xyrnsxkk2CsrnPPSuCcJY05rCXlIEVyLLYR+ulw27O1JHLZdrRiYJCpvWtVklusTFEeLg7GYLSUk3JIiiUTfN+ztXmVv9yo7ly/SNU0OjbCxOxxf+GPS79jukYGiYBRsu+WMqHXibwDAGH4RG1p4+8eVcUNY5yRiEJXemxlp3+zxJxVT9+5mCKbEIxG69J3A1GLZsLe3x+LwkHa1RBXyWQ8wdXyceKDUk5kU+vQSw3WuoypLJhNJMFmb+xznC3fe0fZCUayqOt8YOZ1TFLXPrutGN76eVJw6fYpV09C2LSkmFotFbskZufKerzCbb2GsqOY+e/XHWa4aXjj3D2B33WZznPokMvne+8x0OU6xS+Q2p3q4ITcbw+K/N6MsS8qyJCZZ/NZaZrMpdV2xu7fLbDqlLAue2flRrjz9VQ7299m3JU3TUNiSlOO3znXE+V/H1jN23nyDg91reOdkUYO4/1VFPZ2zffoMMcFqJUV1KUqNbgKqqibFwN61K7x8/ussjo7wfZ9rI9KYwFV6vcBTusmcDY8N06zyoh2l1TdsKbUhCaLEylZay6IXNMldyZY0eeEH5+i9wzsnied873SWBZcPuHf38q2M+wFT7778o4QYWK0aCmtZrhp29w8Y5vXuYOrejbIsUUq+F9yIqfY7fo+iLNlupMHWSZgqqjnaWC68+QYHu1czpmRtPcDUjeM28vW9VO4Cp09tc7Q4JKVE7zqxqJRCKSn8GT9GqVz840g2MZtXlEXJ+hKGG67o2o7FYkGzanDeszWfw2wmCyElTO6prZycpG+860u0bUdakl19nXtyML5/DJFfqr/Mz/Y/OPb4GECRBqG26xb+8Jq0ebPuwRhwO3y34bGBffPmk79GtfPjhOD5+fdoPqoSRWmZTGrpJ641MYra6ZBMJYBbtaikxoU/qafU0yn1dMbWqbNMZzO6TloJD/FUpRRlrolomxVd29E0HSiNtqIhBWpNhxxc76RzTPh4z/CUshUc5KBcP5+OvW6kMg7vqQZ3P24EhbNlrBRapTHm651IhKessrvmsAxW8/037gdMXXzq11EKzp7/ME0rIZ+r7/0nnDv/4VtiarFYcWp7/vYwxUlb0J0dI6ayjtfw2ICprutwrSTl+0zR/sYwZUAlqQt6gKkbxm0KG1cSw7V2feIhHx5TJEZPUgrn88SoQRpCo9G5P3Yh1bgbVo8ZNKiiKHwOSS1bFPl9hWURgnRVk+vWhBBwPq4nPl+4FvNIqk3HSVgzVQbpbunLkFApjt93eF4sPsCs/+Zus1LGNZDYWBCKlOJYP7A4WqC14uiMoa0bQgzSftRLPN2nKDUICoxWFNZy5vQpjNK0fYvzPZPZjMlsi3o6pZrUmKJADdXAgxebL7VpVvK+richld3amHUYVhpMrBdWAhND7lk9XoIsWC15rxTXm8+apZfGD1+HRPIfj98p8+8VI+CGkAyDNMaII9mI08Zj92HE677ClHfuOKbyvN4MUzLeJqZYP3bPMHVsk11jKmxgKsRAXU9ugylNYU3GlKLtO5zvqR9g6qbjxANlf/+Ahx56KMulHNG2LUVRUJUVfd/jvHyYc+u2lyDWwHxrm7KsKKyl65rxtPTey8ZXlNiyoG07trbmTCdTtJG4pXMux++8VHVraZ0Zk0LbAmNLkg9SGOZ6lK7l8hVYo/n06qPocuDYC5g++95ytJY+85ITgOohAba2uIbfP/tsyU+/5LgXY3Arh+G9p2kbzr3+Ib728Ofou5b/7E24tr1Ns5KWscvlksl0RgyR/f09IDFLf59z1Tmeff9Znr/w3ezu7bJ/tMepM2epc6/yhCisCvIkOauQ8EnvOo4OdinLknqS+2STUCmhygo0Imc/bDZZ1JMIIVd4g6wDPYjyJQheersQcw5go75C/osZHGH4WigY+08MyNM5mazyPdVaE/WGFZUEJMPrN2XM75dxP2Hq1Ue/sMaULkkh4vubY2o2nW3UrcTROk5JDqnBqr4VpuSxm+da7sa4PmI0YGrnvf+Ew6sH9F0LCk7dBlPWaubzCU8++S5efeXCA0zdBlMnHiiPPfY42mh61+dTXUIozjtWbTuyUKqqkgrSMV6naNsVzWpB3/XiVlYlxhS0zQpIdF2H956HH3mEorDEFNi7tsdsKrHk1cozm81B5QKvBF0TcE2LDw2fPPoLuPlruDjD8n5ZRKxd7c2F9UvvLXnuJbk5n322XMcO05otJgBZS1A892I39py420MrTdzAmXOOv/WY56+GMzzy8CMslyv29/dpmp7VqmG1WlBNLNt9J42BmhVd07CwBmM1ZV3zyPwrTFiiqw8z25pmyQ5IaFIMKC0Nmh579FGCD4QYcd6jsvKtC1DVNTEECWuYREhRhAVzC1qG/g4RFKVscFpjtJFiVCXNn4ae1qMLrdaLdbgP4sr78d7JYwKOFOVnYT+J6x5i5DBq2rQgOL+hSLE2pcZ85X007mdMtY//JuWVH6N3hkcflwPlVpga2gWPHgknYUos6SHUfy+G1oq48WHOOZaLFe8PP8Xrj33xbWHq1JltdGHQlX2AqVuMk9WGC4sPXtQ3Q9bQ19I4ZlJPcpMgSdZUlVSKCm2xIoFUAeu1pWWswRYFq9Uqa/LDcrEk+ICx0vCmacWaatuW2WwqrpiSPg+PXfhO+s7x8/r/5tsnGucjvQuUpVQCj4t4NE1kBp57qR9d8OfO9/ziMwVKwc+84jHK8NlnLSFEPvVCR9Rx9FdHuiPcdVd9nYwTK+FM+7sU9kM8ceEH6boeHvsiITiWywVd13F0eMiknpIirJZLiX966WmdoohUG2uopxOqusQW5Vi05YNQK+u6ZFLLPUsp0fZO5jxGIpGQpGNkCpHlwZGwkFDEJBRWYYgkfAwSF9YKpfLCH8I0ORkokV11bBPaHLJp2fGXlOdiSFgOVjFjXD7RrRpc33HcEVfrf5Qa2Sz3y7jfMNU0C7reESNMt+oRUyGcjCm1gQ+tlBQDKoVVYJSR+5UTvjEO+cl7ials6bPGVFWJd1fVteBNqbeNqW3zBUL1mQeYum7cpsGWKAL3fZ9d10HDX2c6ovRaCEHitVoLxbGsKlJM+DzZkuDRWcLAcnR0SAwBrQ2rZkWMItdtrMU7T9/LZ45x2sz5Xq2WuN7jih4108Qon+3z4g8hEGLAMOhu5kWVY8sxRbQxI0UyhKEwSSyuEALRrDnzA0tEYom3Wb9vexy/O0OHtzrPr7XStnS+NaVZNSgFru9ZHHmmExGia9uGupLOb8F7EpGYxGKqqoqyLDG2ABShbVGInlSppfCrLCSh2zQdbjbB53lsXc+prTnJB/pVx2RWE2KW8AideN8xZrdYNkFZ8OtNcdhEbmXZDNx7pUAre3w+xkN2mKo0Um4hYYtiDMOsKZHHLem7eOPe1rjvMNWs6HsxrFBvH1PDZqhgLPZLMRJCzPH8+wBTtdT5WGtISfqWvD1MCTPTFw8wdf048UDZuXpJNIO8SAGc2zpHWUmb0q7rWK0cSmnmW1tCXTRaesfbzM02FdpoDg728EuRP4gJjDYiYldKo5szp88yywJs2hhWyyWofZG5DzEnDh326Ahraur5nMpoFBGixztPNPD6479K17a8/+qPjxOilFQh/8LTlpQ0f+2C4qe+JtZHb60UFD7f4rzjtSe+RLyyPsH/7tOGn30l5Ljm3Rs/vPM9YilM0qjjlQBjDJfe/WUWiwWHlw8I3tOsGoKPdF1DeijkojfF1va2SJsXVV50EWU0Rlu0tZASrm249NobbD/8MLaqssUjG0WMkd73NE1LIoJSFFVBWVeEzpMi0jQogg8iHxJTzAC1FLbYKIrSiMzEhp2zNhiP2T4jBz//LK/NIhDZOh4WdIqJ5eJIaJeuYXV0hPedtM3dfM9xZoe/v3/G/Yapo8MjrK2ZzufURrP/3t+knVY8vPoJooHVSthJZ09tA8cx5b3UTumiwDkJrcSMqZi7Ga6adqyhSUmkZwpr7zqmNhPVI6YyUcE5J5g6eJuYwuImz6EeYOqGceKBcrRoMEpT2IL5fMapM2dy7PcI1/cUVk7iIrMWJCYnltNquaTvO1bNCpIUG1lbEF3PmTPnmEwnVFVNPZFYbdu1VJWAxZYFZVlirSH4gFKekCfC43C+G20l6S3RcOHpLxFWPvOs17HEX3jG8snnRdY7pUiKSuQmYKRHxijMlxACRkvc2ofAc+cd5Crl4US/G1bVJhfdGE2MYoForXn01Y+wtVzSPPQPePjhh6QQMileffU8R0dHFEVJCJ4QAnVdU1QFh4dHNG0vQnj1kmsXW2LT4puWdrGg2toCbShL6fAXYsL7kAUHJZxiCoMyel0ZqxSHh0e4EMV6RY3hGa3NODGjVTOu+OHf4xN3q3B6IpGyGqzSiuj9aD0poCgt26e2iGFG6H2mXsrfhZRIMcfsR0va3ORTvnnjfsNUiBH8cUyFjKk2tBJiuw5Ta1HKtbdzIqaMQUQVwzH83GtM+Ywpay1lYSkK+zYx9UlWFy89wNRNxm3k68V9LYqC+ZYIpw1uLoA28tx0Kj3Ju67F9Y62aUaaorUWa0rRujHiOE+nE6azOXVdYwubmwNFnHcoY0gpiYQ0a+VOHwM+SZLJ+x4fIgZxzUNoWS4WpBgxSqqCq8yjHhNSGxc1KLYmpAbER7HY0iajIa0pjkOi8W5kFI8TJgZ2SCKEdSfGIV5eFCVVXVNPJiOwtfaiUaSFez7ImccYCd7TL1eyMJoW3/bE4Mb5Xl+jgE+PlGt5HxWFvhqcRynwXjYJH8UiFikJtbEjqOsirwm4sRBujMEOVtRowaYcFgkS98bIWkvrdgWikltAIovVaaS1UG57a4AUskS8GfWu7pdxv2EKEiF6vBNMaRIqRLquZdUeEWPEaI3zWzdgavOibo2pDWbXNxlTflj3PMDU3cLUiWib1DVaKaqq4NSpUxwcHuK9o7QFQeWTvio5dea0FAz5Htf3rJYL5vNtppMp8/kjaGNETts5TFVQTybUdUWVY5plVRFj5Nq1a8JMyAs3hMB0Ki1re9cRdZIb2re0vcOUlugjl574AkcHB8QYMNrQNCvqnNB87nzPLzxbgI8M8ssximWmYiQhfVec63nohQ/Cud/NN0bxufdVfPp8h0pqBOPdHSLL4b2T+XT9yJRJQNd3JKSNrLXl6JqHELLsQ6TtWmbTKZN6QrNc0e0fYrUG71EhjFbOwL6JIUKMaAVVVeQYv8TcNVrqElwc3W6twQzvMSx2RU7pbW4P8tt6z0gbAd+BLgLkIr4QRN5BGz0mDm2SGPVgVZIEGCT5vionCdEWpUwWPQS0o6prrC2wxf11oNwLTD300oeydxN5/vSvnIgppSLRB1zf0vROksQ+8sbjX2D/6ICzL/wVjNHMZvMRU5I/WW/Mgz7ZJqacc3gvm+a4wefk8aByfK8x1fed1JS88FeYNC0Hj/zDt4yp4tRfRVclYbmi27nyAFO3GCf3QyHhvIcOlsuGhx5+lLZtONjfI7YdtihAiQT9crVkcbSgbzve9dRTTKdTKd5KiRB7VqsjmtWKSV2zXBxSFIbtU6domjYn/oRx0HUtSkm1rneSH1FaXMFyOqHrAkobfj7+Ph85XaKMojlYsFpJF0hIvPDYL/Mdzc+KtWcLFPDTL0lRkbd27MM+TJ7P/e2NNvzQlb/EpK5QW8IIWwu23b2Y72ApgFgsIVfC+uA5+JbfhpT49hc+wwvlr6AVbG3NMTkRKpTMQFmVEht3Aed6qkktjBZjcYsDgtZEW2C3ZpT1BGvFItFGr3WlRmvO47oOnYxQTg3AEYPuz2h1ZrYQY8w2jUs+JUTPyOqx+Gqo1I0kUhDuvsp/Z7TC6ALX9/lxRWELqZ1wHc3yMH9P+ZTohdqZgPn2KcrJFKOlgG2xOKSeToVTf701/U0e9wJTV57+KuJ5ROLByZiaTSf0fQRlSP0hpQ0or7i0+kFW3YrLj0v4o7x2lTqHz+S+hNGb9yHcElPWGPrg5Z6SkfRNxpS1hvl8xmOPPsbu3u5bwlRyvXTMfICpEzF1svRK75hOZ2zNtzl95ixlVUkRVVEwNZZEou872nYl7rLWzObSUnZwEeU1PV3bioVQWNquo2laaW2pleQtcjHOcrnAGENd1aCkIQ4x4fqenXf9W3oXqfZLMIlVvyClSB97VitJtBfWYozmytO/wXQ2411vfJznznsCQHZBU/4srRQX3vUlSepHYaN87v01dVXy319KYx7jhq6bd3SI9RhC4Bee1qyaRLMKqEtL3nj8izz29Y+NrBmxNgxlWWCM6JuhxCpqVkspeisKkYdAjJWgFNWZMxJLr0pUVeV+5BqTE6MhyCHUNA02F6cprZjN55RlSeiDhAzXkYu1jz3EwdeXM4JBqpMZ81fr18sfSc2FHjWDFJAKK7pT3rM4Osibgcf13Zq+moS54/pOhAxNiS3sKLyocvMopTXqPkvK3ytMPfLyRwgxsLf9uRMxNZ1UWBsJUZFMYi99jOQSfWyEipwxdfnbH+HRq0EKI7OsOXBTTLVti3dOPKNBdVeti+LuJaZC8DI3bUOzWhGDH7srfiOYSmqdEH+AqbeZlA9epAm2T51m69QpvBM5Z6U11mrarAPUtS1FIeySST2RuG2OBYYonc/6vscHL9WjfU/XtTTNiqqaYKxBRSm2Wq1WFLlxkCmKLEHi6LqWsrBonagqCwbafiWuXRK5CWvM2AchxJilJTzrqs88wUKvAKVFujoEsfpCQFFuWA2RzPR+a+v4bYyUyNcoSUDXS7iLtqXvZSGYLMftg6fUBptbjLZtCyS0UXRdR1VWVLkXA4g3nApDdfYU5XSKLcXCDFEkunUGzgC+3jlMVcohbw3T2RRrLdHFjSQUSFx60/U+/pzE2LNMR1bBHd5g2IeGYr1hrof4+6BrlGKkbVdCO40R7zwhDtIWKc+bH8MoxkiBoMp5sEEq/O7dubc37ldM+Sw7JJjyt8CUhNhCboN7a0xJcSApEQaG0jcTU07mRhqTqVHyX2Ro3hqm3EDOeYCpE+/ciQdKVZZsbc3Z2poRo2e5XLJaLmhWS4LrWa1aSDCfbbF9ahulFT56msWSc2cfQhvNarWEJFxnRRqltpfLJVy5wsOPPipuPOL2WSOJRq0U02nNtZ0djo4O6V1PYQzKSCc6pQ1t72jbVXbbItaWVFVFXdcE72jayKuPfoGnLv6wONjZfRuEz+qy4tz5D/L641/EOc90saDe/x3m0yla/wDBSzIvkUaNrzs/JDQRYuS58z1/63E1WjOTyYRr7/1NUoKHXvowzWoFE1EvlfBghzGa7dm2tBmdTpnNZ/g+EAFdWCZnz3Dq0YdH7aeyKFguXa5NcGgjLJy6rml7oTiilbBbCkvwPjcggiGZo5BwidFmI3wxkB+kz8ZQh5BSYrY1RytzHcMnivXYdri+H0kIRVVhlMHYgqKqKTYQFvy6D4PvHV3TSphFq1HyAzX0bF8r9t5P415haueZrwKQ3nirmCro60/T7u3Stg0xheOYqmpef58cVE+fP2I6nd0SU23X0Xctznm0scxmc7SSe3SvMQVSeKlzyG8ymUhOxUXOvPC9vF7/nbeEqWUqiKQHmMrf6Fbj5Iylhv39Xdp2RVVPaLuWphFXmASFLSkq0Q9arpZI5WXA9T17e7soraSAK0ZSEkbJcrGgKCqsKSjKitdefZ3tU9vMpjMm0ylts2K1WrG3d42qKjk6OhSxOwQYVT3Fu5KyKIhexN5iCjnhGGk7x+tvXMJYQ2EL6rpieepXePTVHxhP3Nce/UdobZhMppw++l6R5U5w8alfx+rHMVpz4VvO8q6v7bJOjR1Pj92xkcAoTcqVtZ9+sePoqOHlh5ccHiWRy9aac0maJWmlM6UxSl6pLJhMamazyahQevahc1xefowYOlx9vAAAIABJREFUAnOrMo0xszy0GsMnTdNQlJNchSsVuKvliqSgqCtmbk7ykmQcZ0Dl/tIpSUPTHKs2ZijAUmBFL0istOxaZwpp17YiPbHh1w/FW7aopG5GiXCeVutYtFhpayXUEEOuIpaNwhhFCp4Y/QZb/z4c9ymmJtMt0XXKTKaYY/GCqZ7XLwyYsuydrZnPpPGUMaK+u5yLYOVkUvPoHxxSFAUATdtxans7x+KTvP4eYwok8dz1PUdHhzgvEvRbW9u3xZSvPkWja86eOcP+/oKkNEVdPsDULcbJIa9cbOOco2kb+l7E5WIIkBSqUFliIGY3149UwaZZCec5q5saIyewdw6FaBm1bcPR0ZGchCmhjKHL8ePVcknfWZarFX3fEVOUBLteq6cOLqskoDQxgfeRyzuHMinGUJUl9WRF+/plysKyvV3jznqMSfS9nMY6Jyh98ASzFlcTpsWdTx6utXUYC65SdmvFTZdEWWHtSEXsupbFYsFkMqGqqnEh2wxyKWorKGwhhWPZbVVaxAPjpnQ1Ur/jnEMpaQ9rElRFIQwVI9aJdx5CIoYhASgLUpuhIjpbMQphrqREUNkC3RAFDAPlMic8RymODJAhBGGMPIcKkIQyG1PKrvtGz+u8roc4OAk0iqxLzVrfiA2r6v4Y9yumqjqi0lqNeEjqCqYSl3cOUMpkTBXUk6Wsu9KyvVUTo8MkaTcxYkrrnMfIUi4x5u6F3yRMIZTpYUN9K5iiLCkK+wBTbxFTJx4obSeFPMZr4irivXDgq7IkpUEJNY09m/u+x3tHURR0Oc6nlVhU9aTCGkNMkgtoVhKrbduewpp8Qnr29/fpW+HexyDiar3z9F1HWUaK0pOMtPd0XsBolCIC/+KgRNmSP/Pv/jzey6SYzIW7oM8znRT8uz/7//CxKHHjtu25/J6voNF5kUQ+cuUvsjWfcfRE5I0PnOXJF/ZyB7O3BoA1AeLWp/mm7HcInn949rcIwfN9jxh+ee8v0jSa7+0NW9vbVH1H27a8/Mg/4uLzFzlz5jRnzpyBJBLjxsjCGeLtVTXBe5+/QSTExLJZjjIuQ0GTcOsdhbGUVrjns0mdLSNLWZb0bYdGi7sdZfFZLXLqpIDNLn9MCe97hi6BwYtWlbFW5MFdGPME1WQi4IhieXdtR3SB6GXB2xjH2oyjg/1js1iUIpiojSQHh8K/lAIqKRQG1EAP16NG1v007ltMRdl4nXcbmNIkwEfFGxePbsCU1jCZFHz7tz7Jqe0JWkPXdrz2vm2RY/GB8l8f0HZCHKgqadCljb7rmArRbyTl27VXsr1N3/eCqYf/4W0xZSdSLPoAU28NU7fR8gLnRBqgLCvqOuc6SBg1fInMQ0+DOxaJsaMsCqlQRayeFIbTWJgug4UWPDzy6p+GBG888q9IKuY+zXaDvCATLOtY7BtbWLSTyQ9DYnBkKyhIisokzlSw00R8VDivsKYYGScxBtpOvBTnPNeuHeAftzz6yBb/yUuLzL/W31ACMSWRwW7alkGUTmk1NtDKL8oJStk4dvtreO+5FAL/+e7fpus6rnjP4eEeRSFc+MPDI46OhCa6c+WKJAxVKRpkMXBwdEDTtbltrOUoHhEV6FK45ilKHLZbrkhU0g4gJomb5mTf4mhByB0AV8sVMVcKGzUIzEnPi2FFNs1yVFUdCkMH9kmIYVTO9dkKH3jxm9LnSmnUBohIAzXSUE/mDFXFwTuxlVKEmK3vbC0pY0laeoXYqkIbQ1HV3Kzx0zd7NOYT4D5/1zG12/4IAJP4907ElCs/QV+eoSvPMc/aYYKpiGKtc7eJqdMVXM2Y8l6oqEPBY4iRpmuFMeQcOw9p/uOrB9RlQVWeHWnFdxtTLz89w3tQqmc3dHSVx/nAH6XLFNOCWCcOr/1lrrYX2L9ieGOvoOv+rxFTK/OTXGnPUV67RllYjCloOv8AU7fB1IkHijUGbcR1lXhqyEt/cJeSyDYrMzbrGawESRBlHZ241tIZ+yMkcZ+euvxf0PeRlBQxaVL0WeWUtYuZM08hyy6jpXAqDpzxvOBjTCglbIVCJyoDtkiUfaKPamR/LJctmQch7XdDoO97VsslW8NN5PjCVyes/5QkRvv8UzWHh4dcbK7Rm34dX1WapPLNzm4jg1uuIq+//gYxRl5sfkzqcmKk7H+Zg/09VHZB+74neNFP6vqeiFT+tk3LHvs4F0QMMOso6TOH2LLEBMvSZbXl/D2n01M45+nbjjcvXs7V1ox6TAqVdYYiKSSSkQO7y42blFYUZSmhC63XjXnyuthc3ClGXO/wwY2hxJjXEUpRVlJotTm9UjnuCcGN70GM9F07ri+tFME7tLUYYylKkfqOQZLDOlvRxzad+2BYY7CDBPldwtSST+I7kRmqyhsx1ZefoqeD9u+sMYXawNTQv34I/a4xVRoorsOU94HFsr8FplbEUL1tTC2WSw4Pj/i3Z9w3hCn/+t4YLh4wlVLiYL+/JabUBqa6vT2c85kOLEWik/n2A0zdBlMnHyjWYPQgTJbL90nZB00EEilq0NJdbGAgJHLVbC5wWuvqCChSXgAqKWJQBJ/yYreE0AHyPkZL1erANpA4IbL4cyggeC+8cZ+y2qq8ptCK0iZMAXWhCE6slxCiUAOTiPOVZZn7FjihcCa56T4EDFkq+qSVn0fbdly7tuLSlcu8+eab4iLnnKNYekMKjjXlL4lMw5WrV4HETrgqh6LWxNCxzO1hB4SlJIfqUD0fQqRLfQ79BZHUUBrvPdt1QwXgHc1ikWOtwz2QQ6fve5pmIXTF/JV0TpqmmKQnQ1LSt5qE6x0h+hy2MKiNepchyTpscLJGcww7+DHmS0p58cvcDP2sh9caLcnUGBOu6xgThzkOHzIV1OrMPDFGwhS2yEBJeadaN4O6n4a1hiKYu4upeBtM6aFfyIAp2dx6567DFMQi3oApXUB1DFMB5wdMkTEVRkwlqrwO3gamdne5fPkyrx113xCmQKY05fyCyjUUy8XBLTFVbmLqaIH3MWNKciYPm+IBpjgZU7f1UFTu3hUzNVAOUAX5AmNIpDC06ZVTMaRE7wbZhSFZJqyUlHQWu1MYU0j5f3AQI1ZrXAbIsDCUygtEgbEmC80p/kJ1yOX9Fc1qidEaaww+espCeNPziaWuNFSJLcAvPH0UV9IYK+G8vs+sGaE5/u9+zg8Z6F3HH72r4ukXD6nriVj+J1ZiJV6/8Dpf3znkzTffxA5aN2r8n3GspbwlFm6M5s+c+jgpgcvUQA009qdI6W+jyFxwjdAsAyQX8X5IlxnQItkQc9OeqiopCqnyXR4uaZZHjF9IaZZHRygttS3GFHlji3RtQ5/lXkD6Zn/X7h9ibcEfPPwtOaQg9zLGRPCd6BBl15n8XAghF0Xp8TpTzg3EINcfc3y7WS4YahpiDMzm21hbQlIc7q5ZdiklyqrGuaw7RaKsytyESuYnhWyF594RKa2po/fLsMbgik+jUBT95+4Yplb6JzMRpcBGC8ZBioTq07QciGWvpBZC6go0XfkJ6owplKZrVyxXy2OYMkWNseoYplSV2AbCBqastbJh9T1KI3L5XcdsWnHx2XM0p2bUl/YpbfGWMfV/zle8vLPDm+ES9vAbw5TMD+MmrJHQYErcElMr/RPY3C5AFNIGTHFHMVWWCaUZVcXfSZg68UAxRmfWx/pNlFbEJG5QiiEzE4SKNvyXkvytQslNy/52zOylwb0ySqGMIiotTAaAFFApSrV3lOIk7z1aQWGGUEEWqMsLRoqoICTpDDexcGp7wmRWkkpNah2dX0Ljcb001Am+59fch/kJ/S/GBjsxznjjwgUuvPkm1mj+/WRCGUqqsmQ+32Jre2ukVU5nU97zongQLz8zo+p7dKWoi2KUfh4Wi7j5+aaj1lad67HFlH+5+wViTPyZ7Y+LO55dXC38QQaLQo+AMdIJTg/FRgrfOxwJrRX/y+wT/MSw3DOYgh/agoI9fZaiFEnuorQj42Q+3yIESSz6nBSOrFkz3nt8EMl0ohAjgvcE3+ek38C+83TNkuAc1lgWB/t41+VYryxynROA7aqRXuY5xFLZEl0ptLbEvmddPZzQk2lO5q5HIve7UIakAkoN1n6WATfFSUv8no9NTKVeZE3uCKaU5BiNUgSjiFoTAtTicqNSkN4YOXF8A6bgppjyIWBT5H9jwXPbj1PPSig0sdvAlPN03YrgO2E5aZUx1WNMMWLq60bqQAZMfeBCz9bW1rhmptMZRe7/8/IzM/prPVq9PUypTBmWA+7tYqofMTWbzcd7+MfFVOKdi6mTOzZm2qpSYlmF7OrE3IUtxiF+Obhl8hhkXrXMkeRi9OCGSvwuJEAFkjIkI70GXEw4L0Jl0SR01FluYqgM3bjofOKTRN1Uq6EbXMIqRArCe1LSJB/QRIxKmQXT4F1HFxpWq2aUrEhpmmUjhMZZ5UKkqipZNS3LRpJq3juxsi4dQYI3J3POHh7hajVaEOsvKtbA8Igawr0KwvC7kgrbTYt02FSySTrOPcOzGzmmYV5lPjJg8vPGGIqyQhvxMCNgbTG2l7XW4lKAmChK0SLy3tHrLmujrd1v1/d414n1NZkSXI/rO/quGQ/5gcIYg8dqS/SBvu0IviOFsPZ0bba2Ut7wEEqnsUODn4TOpPzhGo0xRBsw0WBUykV1wurpuiY3dBKGSggeENmI+2ncXUyp45gi4qL0IDkZU7m6+qaYAlLCqnQMU/iAIqIzpvpeMBW8x9gyY8oxmRS3xNSZnZ7VakWIAe8ck8lE4vYZU22mV789TOXr4g5hijuIqTFS987D1IkHSlkWDL0Pqqqk7bosAT3kMmReBo6yhPPSGCNVSmLERWHF1dYK4hC3DYSkOH/u3/DUzn8JIdE66HpPSh6tpLFQyAlCnWOA4n4p6SeQv0QIkSJbMOL9RNpVg+9aWQsp4Z0AyDlHk1YE19Glli/aD/GX2l9ZT1aQxd21HV0XKApDUVq6tmNvb1eE1YQ+wqvZIvGv7PLaWfCrfpwXGLSL4pAvzHHuNB4gJjPIFElCenmDyMsZX34yF2eBaX4pA0cWeMqLfACAVvBV/UMYo6mV0D210llscAOQSpRVlTYMcg7fcuEPiDHx6rN/eqzUjXGIF6h8LeDalr5ZyuY03yK0Df1qxWJ5RMqHGErCKaSY+0wk2YR8yJLaOZwJudugIUVZ2PVkymQ6AyRmbctiXEdKKWxRMHDtrYaQwwHe9SwWhxsbjMJ7SZoG705a4vd8bGLKTH8WvfiFbxhTjflJZpMJvrRgLMEjc4wnJIWqCpTVoBOtW70lTAE3xdS3vvhzTKan+BvXOrYua6xR+V5Hdp76WbRSolm1EkzFGNG2pmulUnsy4ZaY+n/PVWiz2sBUQ2nWmNIKfP/2MCXbZ7oBU0YpwRTIpnsbTA21N+obxFT0krPSWt+IKd65mDo55KW1TFQIoKGoLMoblB8ULfX6A7OaZcp5M51zHSYpQoCERZuCr6iPgklUVc1sts2PvPAybe8IMfKbfJTv4eckUZQihV2rf5aFzc2DJtRmQhkq6cOcZQKGU1cpWHrP0YEDpTDa5HBdoiwMMYXMxw9oq3HOZz65oZ39AHHRE4Mkyd5/8RVeeOwZXL9gcbiHGpel3GVtK4wpsWXNfFajbULFwN7ebl6Yspi+7corfP2xbwE8MXZjeCFmS6BZrkAp2qKBXBCmjSUGz7dcfp6E4g8e/ilm8fOkaHhm58/iguPNJ/4PiQvHyJfVD5KCw3tAG7zztE3L1atX8K4b5TeM0RS2wtgCH6VLXdM0pJQ42NvFu1bipcYSskosGZhTq9CI+10aCEbjjZZY+JDQ04aoDX3XgzIYazjz8CO07Yq+a4muE7nuosAWlSSEFaI/Zi0+JyiVIi/+bGcqJcnCkNug6oQK2a0PPaQptphgjWixhRhwocX5/qQlfs+H0eYYpuL8OaJP2OZzJ2LqN/gYtRFNqO/GHsNUJFe8lxWz+TaXdj1d7gtf2ZzQvx2mptMsY7TG1Lee/3n09hmUgpX3LA5Eq2vA1O45T1kYUq7kj1nJdxNTWhsJy2RMhTiBvv1jY0qpCUpFboUpYywK8M7dgKmkDMIqTWgUKVqIYI3CGjViKihFShKRICs1v1VMBZ8gpuy5HcdUjBFj3pmYOjkpX07AJGxKvOflI1nESZGSzdXldkze1bnAx2fhMbw0v2p7h9Ka2aSkrEr+h9Wv8j8//nHRxbE6N6CJKBJVWfB7+lNy02OkrithMAXPh9wX+P3VjLmtmG8F/qU7xXfN9hGRs14Kh1RBXZd88TtLvJOYYlVNQEHfdaQUeK9KfFV9nJicJN4yz1+0hqTNakqaRCBGxe+GFVZ7wPM9Zpar9Idq0UiKDt8FjkIDOXmmBqtCfGQSBQkD5KpVUrauxJ39c2ekZqDv3RgnR0XJYURh8AQfaIqfBGVBP4/OsXWVJHkmjA/5vGoEVsT3PX3f4pDrM1aaL4WYWC6X/MbhRf7H5RHGFvz63iX+axcpypKqlt7aYygmU1aV0pIczJW9SkvMWOXCKLHcDORYcYIsgKiExz6ZEFw3ivSpTJ9VQPQ9pEos88FslokcQxYM1lW2TIfXaK1JIeJ9DzESdSJGx33H8ion/E5yIn2eguT9NKTZp3J1uahlf7A6TWVNvo+Bn4mJpORnwZRhOplQVQWr1Ypn//BvUpUVp06d4exVR9NKsnxrqgj+kBgFU6/8R3+Dwnu8d0Tf8x2vfpb53ml+cfLX+e8u/DKPXXwzt4PtMdZSFgV1VTKbLvAuojVUdQXAf3rx75BSYP/J/0nuYzKI5T1gCrQ2xzDle4UtDFZv1HK8HUypAvDcClNK9MVxPtyAKW0gKcGUVhrQoAxaZxmn6zGFooK3jKm2WVDWU6wpiMHRrA6PYUrqdVI+SN5ZmDr5QKmmqJhQMaFNT0gma81orNG577FlUpZMqhKQDWiQb3DeY61c+KSuR/2tsigpbUFpC+aTCq3kxs2nE0ATo5cq26qU6l3nKFYVNisBhxCYzmacLs9Q2IKuazFaM0szppOac7MZfd8DQgtGwVJ3uF4okAoFQZhrZItBaYMxltm8pigcq0ZcbWMs1oBOiUIbQlRERJMoKogpEIPDuzCEReW0V7nASGlQFqWtxJyzuzwAwA7Jxph7TpcVxkgsNHg3xntHZk922Qf970TKUh1S4Di40kPsNXifwyGbseEoB9RqyeHBPq1vqSpF33Wsmp4qBLQthNqY1odKSqCsbAZKD964xIyV1eKio9bhAEW2jj3GWoy12KKkWeT2o6NXKVZRimJYbASZh1jFuPo32fVD/YHKlcYqQgqR4B1JJ6IK6/e5T4at/n/23jvIsvQ87/t94YSbOkxebM4LAiAAgQCYLIkCQAIkwSSSkC3JVMlSWSWX5SpZqnKSVZarXCqZpWJZJUsWTVG2qKIkCoIIEGlJSAxiAkDk3cXmvDs7Mz3dfeMJX/Af73fOvT1pF3lA82zome7bJ77P+d74PEMy5VA+0rYNhIQpLfxJHc3HZDhhmMuLO6QXtPPuEkxJt1RwgdwKv12eZYwHCq0kChkPpZU8JAqX0Wgi2GwbquUcm+UoNjC1cwmmRiOGw5ITuyOZ1VAyL6GA+aKmTYuMUjLwFoSrRWo0Wrzp0XjSY6pqRXeow1RQ8cvCVERs8MvHFFfAlLR89ZhK7zK6+uwrxNTscJ/JtiaWCt/ULBeLyzDVRVN/2DB1zQXl3oOS1aqirmpWAVqfBmKiR2nIMs8gBAba4mIj05eJCt5qi1VaVN6QDmadDPr/rD+G9ZYs5JhTBS7Iiv0P3UP4KHw4VdMQl9IbLzQUI95sW7J2wT8djDh54gTvmpaEgXD4a615YTIm+MDfc59luVywXK6YXpzxd078uBhZFjHaQEgCQG3De+qWOAlkxYATzUf5gaKgVi0Xq0Mey19NURRk2tAsVvyamePR/Fhjed/I831mmLwrjfOJtjquRYa0NnzLk/+EMP4hjNHkWcl37P1LyuFYwOcdD976X/FLhy/SVBXeaE6/6iTW5oQQmU0tb5yOqJuKQSF64FVraYLh8d3fZGQsmY28T70HrRt0GnaTHnXpFukoI7JEQZ7nBdpYUQJshYoj+I7vpzN06J2QvlskoIsCW+bkmbykSDVcrSU8jxtgQW5BAodmMB4JRQSaZrUgBNd7Ub2X1HtXGhUDxqw5hHqgpM8L51BIYbvQZWhToKymrTU+tnRU6dfTlm3vwszjqoq6bnpM/bdP/VzClGWQZRwrh2RGX4YplZ5Rdw9Eec+Q33CzOHhFzg3H1piSKGiNqZPn/8UGpmpMMURpy994+p9x8uYbOXnqNJ0uhtY6TX8Hbr/jjjWmpjMWi3l6ccee20kwVQNCkJgVOYPBkNOnTlE3LXv7U5aPPk9RWjIlUrqFMXhrcVGTWYOL/mUxpU1BiLrH1O7uScrBCJKzGUNguZjTVBVl2XL6VTcl9cXI7PCQ2WxKXVfYxNtVtZYmiiM7ygVTSineHw6lvhUjwyryF9yZV4apkMgfUzvvpZjqZjti/MOHqWuTQypH29bUTSWdGM5J8UfJICFE8J69uqVKug4o0sq+XjEJXXFKTsV0EY4xjPOC0zu7HJtsMZ5sc+hr6lSkizGyv5hz6ByLumGoLTbdpAv7+zz6zLPUjXSBbJ84xoHVxNbz5Plz7G5tUQ6HZGXJTze/xv2338d0esDnXqz4T3YeoCmErXP22M0U7bvJRhMuHnsVvzj4PD5v8cVx7jvX8t8983Oo6Pjbk++HLKMOisOF5tBHfpEZ2kia7PsoaZ3kQlUqxpFZlBFDfsPzP894lGOKgv3plKZt8a7l9P7/SrzzLzEYDjEKqrqFVrh3xlvblIOBeI+zFbPJmKrx1LXj5nNv4Z/fcw+DMmOsDfvNBYoyI89L/s7uaZ4eDMmygjM33so99ULmfYDPR0XbireaZRlb2zvYqSfG1L2SFakA11JkRd9CqVSqi6XG9BBAxU6wVIw8RnAe6pQq6CPsLk8eRZq0K6oKh5ruPSihjVibq+q0s9PLZPPPHcV3xy+0Wi2JoRLwhShMqSqsFVKvky3g+WuP/l9CENm0khePUTzz6wBT+9PpEUzpCLH1XDi4eARTW80OexfOMZse0LQV3lWEUBPxzOcVZS7F1LppeeSxR/Ct6KjnxpEpi4qBerWCPKP2ipWPsoAS+tRzCOqKmDLGEtpIORgxGhXoTHP60/9bj6n/487/gv/huV/Aao1R8NDxvwmNpLXHW9vyOe9xjad2CKaagMLx+md/jsEgw2jDnXsXJGVXlBy3p8if/x2c8zK4qBU2GKgV1WrBM6f/1hpTWzuYrCAidDeXYqojgIzhDx+mrrmg1CvRNffO94U86Q5BDp5yikvv8Ero1W1uE11zyg3mltV8RaYVymbkRUZ3uW2M7C8WbOUlMS/Jh57FfM68rqmahnGRy9RuTKQUfcSmqNuW5aqibpqkqCYymCF4FsuKYVlirWU0HLKIC8rBgNYJMV/jWikgGoUBSqUpldDfz6ZTVAjk1jLMDUUq4GVFKcRptRMlPZvJ7ycSuVwJ3433bZ+GNNaSaRk2NMnLn81XzBZzMYIQKLKMVbUiM0aYSUOTQmnIzUi6TwJUy5qVyXBBUmdGifGJxsOQmbVs7eyye+wEpyen2NMFTcqDb7VF3zY4iQqbFynPrDBZTieAZKwFJd6Vdy2qHErYm/h7og8E14qXXJayyCRb2DRa6by55HsRvI+4NLy5zomv5wliMuYOLGLvaR8q7Rf60D8dBgWpnz8QvKQ0c531+72etrqqvrkwFa+NKefEI29c02PKIpgaKJm52cTUIFfkuYGIYMoaQnA47ynyXDBlBVMysX0lTCGYUhCDZz5fMp1Oe0xVqxXL1YrcijhYkzrFFIrcJosLsFrWBGUEU9Eg6hYRqzVlKUJY29u77Bw/wfbuCZpG5tgk1bTWB7EpSukwpfM8pehUGhpVRzCldNc19ocPU9dcUJazufSPJ/lIn8b8oxKhIAUEH6jbhuF4xHB7zGA0oGpbjFLYzFIMSqqqxpYFw/GIrWM7oKQtsWlazj37AserimqxwhdLzp09x7n5jFm14tbdXXyeEYEsPaBuVRUOf1mxjdb9gFZQ0HrHclWRZzm7OwXT6ZTvfOj3qeua346Rum7Q0fHJ5X38QBZ43fiLjIZjPhBOUFU1udHkf3AHD2lFDHcTgb94+gQvPDLjcFbDDZq3f/HjlGUubAJKvP4QJNzuCqkK+Idv+Sn++rkX0HVNVTXsH+xTJ/4cozV//94/T0x042U5IE9CPyF43vHgAjdxtK1ntljAsmKQDSh05GdO3cokCOX4sCwZFCV/9+TN3HzHXdh8xGDvAsvgqLTCjMe9IX5bovGeecf/3M7Bmt6otDH4IPMGAl7Dwze+VgqXbYVvHb4SXqThZFuMX9ap3hKVRoqeQdF1ksjzAudj8pJ78+7D7W4Rld57+vZKtfHMO4DIq1Cv959SHa5PRyhMplIx9vrabvn03xVb+SbBVCRcFVNFUQBb3PvoP+DXxz+CxvEbumFBy39e7DDKc2ofekyVgxJTaEyeE4EQdwkhsgpLYuMYjsdXxFQnU+sTO4Q1gYjnWx79abxS7B/sM93A1H/9xX/MPMpAYjkYcMcD/7uk0bzn2GTMdF4zmy3YO3uOaA1ZVpJnJcYGGFnB1EAwdeZVN3Lz7YKp/b09lssF2hpMtqbPKcsBbzr7z5hNp/z21k8muWCxbW3sZZjSqQ0Zzx86TF1zQTnYuyAraRQefyEjk3zmbqKBbp10N7i2pVlVEALVYsXWZIQOMNufUq1q6lXNcr4gKtBWukGIcOLMKQoM0Yii2dagoMLjS0vrHdW8xStFXhT8451tyrKgVFFYkL0nJg2CF556jounTgq1RVXT5oW81LUM4rRtS1s3YDVt7YiuYr5a4F0uQ1q0x2EsAAAgAElEQVTOQdsm7jLw0bOze5zI20AbVJVxbNvgfSQvPNsnjzGZjLHWbnSDyOrtgjzkuq7YWvwy/2P+x/lz2Y9hs4xf2K35G8/8P8QY+elbf4piUEhuHNIi5HFtw3K54uwFx3MvZjT1iMnJwN5jv0FZFDy6+z28Z2/AJ+48gQLe8Dvn+BNvuYljJ06TFyP29vapqorlYsHFC+dQRgzbGEte5IzHI4ajEf+LP8O//JUvML1tRm41h+fOM/3kPsYYjr31JtrW8bq9L6C14fO7t1I7z94fnEOhGJ25kYUL1I2ncY7Dz7zE8PUnCRFU162yjrPFG6cbqKM3eRmgE7OW+pzcxojQp+tuBxGIm2Dp8Ja8NufJs4K8HBGCdPZodW1v6huxXW+YUkikG6+CqSLLXx5TUSVM1fyXz/0jHrzlrxGdA+fAtXzEz7FR8Wdiyc7uDsNzD4M2ZHnG6nBKOb9INp1y+wnHJBtjjGAq2g1M+cirZvdT1xWL2SEvnd/jMC+EDVdDNhz0hfNiUIjuPWJ3mkRUuVxR1xWujZJqTPT7ZWkZlpbJZMwgKVHODmecueFGjp04Q16MBVN1xXIx5+KF85dgKmM8HjMcDfnO/X/Nw48+yVOv+evkVlOFmljV0kZtZEzBWqlBe++onafx8jIfRX0EUwEZAP9mwtQ1F5RxMQBSXTbPiLFMF6UIbZsIGoVUbJBZshiJSXPBKoVV0ISQVrSYimVL1vOpUhSrbYFXFmJgmOcUroG2ZtG07GzvMJpMyHe3YPRuahTl8gPSV660dO37QFRJJhPFzx4/zmg4oMwzhos5M6VoswwHaO/4vdVrUL5hXGRMzBZP61NYZ2mD51P+9WRGUb4l4089+Lvo4rtkGFNZgrZoa8lzja6lkyTETnlt3YllNGAM3hh+kLfyMyFwP+9nZ7jD35q8nfnwz1LVFePBiFVV0QaRAzVWk537N4S6pS1+gIjmk7d8mLZueUm/gz8ePLQ18eBj5KMfonGSkpitGia7xyhHQ2KMHFzcZ7E4pKqWtN6JCfkWpVyfFjDGkhWGMtd84oUtNJG3PnWYpFM95373aW56x4AHT96NMRmxXjH77DmUMaJwFwMXPnlWUjiuJQbF7BNnU344YJSimtSYd5zGxIgOMjNA06LTnENnyF3epcOK95Hzv/cCB4eHZFa8aBfE+9x6wzEUgb1PnGPn205h00ukrWsIAZU5YgCrsx4g19N2vWFq78KeeKXJu78MU9oTlcIaoURZLJc8//zzzKZzYbx1Um95w3M/h/INo2LMmy/8KwotnUp/71v+Kn/J7ZMZTbmYU4aXCFFvYMqgrSXLhV5lswAtba5rTL1w7B3UdcX24t/hY2Bc5uxs77C9s8N8JvRJq7oSTCWJXWM0de1pmpbWtdg8BxUlr2Q1bfDQ1EQCxWiE9lIvWKwaXnXbLuVwSCRysH9RMLVaibZK1OACSrUy8HcJpu579O+jiTx0x1+ho4t3wZM3A2IxkM6y1AizianaeerWC69fooqxWiWmD0WmFCbGLwtTVdUynTdHMbWaITJagaaNGKu+Ikxdc0EZFmW/6ksotpak3J8J22YkyoCUtSiU5GfpyNhUkpKUNVHrxBIcYmoFVLRG0ZYan8vUZ55mWqwx1H7FYFCwu7NFfnyXgkIUz4DRcMjO9pYYjhIit0EpfP15IeqFWimauulb/bz3WGMYDAYYnzPOMkZqh5jmAUIMDIcDcmuwRvVGHWNE+UBQCmUM1ko3hE9hbCeC0z1EGY5KxTAtKaU8zxmPx9xwwxnOnz/PcpkxLkfUdS1GHaMMRqW5G2GWNX2u02Qyk9A6ByrSek/VekmPOEdWlihtemK5tm2JEYpygLWmj6CErkN6zDNrmUxGiYpGuvRiqkORaDaCF86n4Ntk/DpxI4nQkPwX0FEKwrk1aGSwLZNfxMSI8g4VAtG1MrAXFToodOoiiz0QJHXTto66cTgvRH6tEwaEvG4wRlG3vqck6d7QMYpGiIqK6BRBK7jOBLauN0wt5vMjmIodwWPCVD+fdSmmvBTLvdvAVMiZ2Iww2CYGj6fD1JDcStMAXIopjTKmFwQLQYSjQuKwWi8o0gqrUgNBRJFlOePJmBtuuIEL9jyL5RK7NIKpTnXSZLjUkNCxNYN4+jrN+bTegYs03qMamd8RTA1QRqff73i4IsVggDVJWCuCNh2mzFeAKXMUU15iicsxpb8CTPkrYsoapOAeI6U2a2P9MjB1beqVoqQb6ydGcit1CiK85FqMNVK8LkuKIheGUeelCwNQWjMcltTOoZRCG5EUNZo03xDwbcRZeeCuachCYFzkHC+2eXY+JxoFFpxv+e9f+gWauuEf7+xwz1138ubTZ2RKHtEd+HWtWC5X/O1sLZ2rFLx07hzn5zOmhzN+/sxp/nJzSA68dqvi3z/0BLe+/h344Bie/b/5ngs3i9wngM4IgPct7VLSYSIPCuM7vouDp36PLIvpWOnJoQhKhjpDjHw4/zSm+XaZZ7GWoii4v/wcjWr4K/6PsafmVH6F9x4TNO9VopA2nr0fo39CwtoY+XNxyFPaJFBpXBtYzBbpoUPdNMznc2zmOH7qJONt0fEuypI8s3TaDR3BR0gv7R9+Z8H/tH+W6fSAN/3ei5CyqcKEqrnnuc+gVeTzOzdJ2J06QJQxUpi0Co1mWJSMhyPKvADXpqE2hauWVJ86nww+iqwpXRguBcUmRBFJ01D+iV2RTI0Ra+S6gk/06RYufvxFALLcyv1W4pWPJxNcFH4m5QJuKawDqrgWo+3Xf7veMJVlNs0qKO65606ZMN/A1Gw6Y7lYcurU8csxdf4808MZeZ6zs71NHmHL5lTDCc/tvA0fHD9x8RmKna0koZtuQvBHMZWJ8uFyuRIhJxt55rFHjmDq1rvvwqf65PPH3sELqxd5av+A08Vpzm3dwrnD7SQ/HLl399PCH+Yc1mhWdY1SMoNmtKYJDSFE8qIQVt8NTLX1ApCalmBqgc08x0+dYry9LZgqCsEUqQUY6Frr29Zziyq4cP4lDqcH3PvEP+KLd/yVI5jybQ2+wtezhCnzMpgqE6Zij6ksgPINKgayVGPCy0gHLh7BlE8a9sSA1VDXTd8xllloHbSqw5T+ijD1MjWUPYpywHA45OSZk+TeUy2WHB4e4uqGvCywSkby92ZzGWoMkaAUeweHYnxayQyD7uQj9ZqjJtIrihEi7XKJn05RuWGwPWC8NaauKw729lDViqquqKuG6Uzzzs98huaWW5hMJim0NeRK4ZxnMh52jg0Qqdqal869xHQ+BU5x7tlnUCjOPmvQ5ZAnP/tR2rbh8J5307z4SYSgT/QbsBUAyn+SVr2RGD3nH/1tBq//vr4fPdlTX99svYSYoHjrM2d4Y/MIeX4TxX7Bp577He5Z5ShVcDZ7ip1TZxiUIhNaliW70+N4H/jB8G3EGyo+OSvQTcOIF+loUIia33xNnvKekV+/z/JDFy6wXKwwqUVxUA6xxYC8GKx1bTptG6V6MOwcO8Y/PDzGxQvn+cVP7/O7J99L8J43Pfsu7n/hZ3nLzveTZRk6n9BlIGKAjzz3s9znvyulJRRBKRpSN8utlnIwQCnF2emUwbHj0q2GDIyRIrIYAqGq8U3SuhD+C1TwoAJZbiUSNOJZZpn8PcZInumUojEYZci1RjuH8wKs0KbJ3o3i4/WwXa+Yco3jyaee5JZLMFXX8mwmk/FVMVWWBVkmg80LDM9vv63XV3fe07TuCKack8g+yzKqVSWsGEXB048+zGg06lvcNzH11KOP4hMLRwgR1QhTsXeec+fOs1wtk41kfHb+6l4UqsxLDlaHeO2hUMQ6cjib0jQN33X6OQ4O67S4C1d7R0EfXMv+hfMsF0tMVq4xlQ/Ii6FgqpvpSK31XbpuZ3eX3ROCqS8+9IXEm6/QUdM2FWZrizzL5P0f64SFSF1VOO+ugCnPwf7FHlPgOXX65v4eaa2kQp/Y1i/FVN5jKpIVNkVC4kR0GPtqYeqaC8poskVWDhiMhownE+xyhZ8viXVD4Ty2btE+oGqNch4PuBiJrgXvpI1NqzQJLJYRle41ViISnqlSXpQ+BLQP5FEzRHNiOCRHYX2E1tMsVywXS6ZNw/npnPFoQgiQ5RkxQpuI76q6EdnOlN7xKYUUuxiwa4NNnkFMw1veORnykyUa0XxOEEoDP52SmTEi/qW0FkEhtxa4MdqgTRJBSp6QTnxCXSoKZALdWqGCVmnfRVHKvWeEd56hH2CtZaxHFHkGxCTzq5NRRExmONjfp6hq8mKAsZa2rsmrFXVVUQ4GwqeUuKFkUI4+fdDUNa2TNEfnBUa1QRYYwbmYXlTyjTZJJ3fnHoNPbLMNvs2IHdCIqEY41XTyqNf1QIU3BjIhrPOtUI2jjeSVtcZkFuUlqpHBK3kWnXocqa01+rVGd9SajoE3hOsrQrleMVWtKjJjLsdU6/A+XBtT3bl0mFKJuihuYCq9hHpxKxKmUIkPy0jb+lcLU+YopjqiRp8WusxaxqMRq+VKXrQ2w9qEKS0D0Af7+xSrmrwcYGyWMLWkrivKckAIHcvGy2AqZSu6P6vLMAUQhZfriphqqdvmCKaqtk6Y0n2ZPaKEnsfoq2BKf80xdc0F5diZG1A2oyhyynKIXlVo5wmrmrGLBFf3uboM0SOpoye0LUWiOhCu/c10i0xhiushutl6KH3xHrBKUaKxUTEsR5JzBEJQ+PmK1XTKn18s2dveoRyMWFY1w/EEaw2LssA1DQdVzfZ4SJ5lKA3LxYLfPnsTexdHKHTv+qiufQ/xLoq9X8L72xJNuHjzsf146pCIED6JRrTAzz3ym2SZxdqMnR/6FuqmppNSzTJLdf+TvZZB8b2397lb7zztRx+XolfreOGpJ4/c829zJ9FacV4/i/eB0Y0jysKxpccMB1LQvf2+V7P7ud/i1M23ooAit+zPtimHKwbDEXlRMm1dGhDLGU12EpFcjVKqlx3t9BOMMXjv+IMbP8TrH3y7GKeJfbtjcIqqqiVsBhSBuloQvUsFZc0nXvUB3vz8u4gRbNihrlYJ0Bo/XZJZkVL97deP6Qa2vvvzKwJKDB1L2wj5ndIBtEVpofcJOg23pYJSF2WJ7QfphmocWEs0BrTpHHQ2yyzXw3a9YmqxWELgMkzVVY1rag4Op5dhKji/ZuKNwub93O73Yjcw5VwrWuhhjakXn358jSm6mQhFnhcYa7A2Yzgc9Skshcx6SFtzSC9xvYEpR69/0jr0Rh3AeY+1WWoWEXG/8cjjSs8D9Wt4cXEWkGjpe46dF3oZDWVecPHiPuWgYjAcHsVUUQimVkuaptrAlLARayuEkV5G/bnziz8DwKP3/jfisHmPVx2mZNFUaJrVsm//VUoTQyvdc8mYNzE1nx6Q2Uz4FI1JWEi8ez2mDG0Tv66YuuaCUs2nNHUNLuCyjFgtWc5F0U0rMF1PQYyp8BSJPmCUFBN1hEwpMiUXTLcYB5KnKx1SRevRIVKOx8S6IRBQdcN42QgvEOBLz50mR528AW7KOXCOp59/nqeffZbd7R1O33CG6dYE5xzn5nNGt90MwbN/cMD0cIpSxxiNR0RVi5hRCLS+wjif5Eodb3z8OO1Q+LCyxIukNMlQWxny62+6iOdYa5j+ysOsVst+SK3zVLrwZv6+zx+5ryEkum3d9du3PaV5TIU+eWaR1zw0BiJPxIc4duwYSimmF85jjeH8s08DIlb22vu+mxgj9XKJRuRTV6sVi8UCmxcS1qZca5bl4t3oVHBMx39R/wmevVuGrIwxvGf3z/Ez7v0o53lq+u28takSr1dgvlhR1Q3GaH7nDWMGF2oG37IDJmMw3OLihfN432CN4kPHpzStIwLl00NJ4zjHY4XjR89tYWzWvwhDFNGo4ET72hgxdCnWqo0XqhRdhefKUTUVmc6EYiNCbUNqp72+Ul7fbJiKIUgL/GJxBUwpxqNx/6KJwVPVFcbL0GbrHFpb2jZhymace/ZpiqJ4WUxVVXVNTG1GOvClYaprUGnatscUSvHx/XH6nch3nXyWwUBakevVCq0U1Uo6yBaLuWAqrOWZxWGSLrlNTHUvZ6UUvmmIRUlTr2iqwOzgRRqvekz51qES5Ym1huAaYtRgMrZ3jx/B1N6Lz9E6T4hIBiJIrTd4x/FTpzE2vwKm3NccU9dcUJ5/4nFsDOSAttJ227SOyrVYYiLaXu9cK8i18Pv0zz6C75sa2QgL16mPqm2ZLxaslquk6x4wriU4T2gaYfKsKkyXVF0ZtkYjTmxtURnNcDQiyzNsLp7IcDwWPWQCzrfiTfkdCWuNkE52BiYToJbhoGRrayK6Koq+yKaQHvDtd7+a5UceT9epmLz7Pjkv56g/9GjyLNK96I0+XfCRPrtNKoTY54s7Q1Ro0ciKadRIx/7lglnvSimL0aYvsiuQQqR3KV0REngCy8VUBtaQfbk8F+ChjmiI/2f+AveXn0Oj+MHm2/iVC7/G9vaWKMmltl2RnJWjfubWj6A1DC8GqsbTtOKJNk3VD8n92t7/S6GgGr67O3G6FusQorxcEyO1tZnc95g6fFQipkw53s12Uq2SWmEIuBaij/jWY6MUrjGdCuH1taB8s2EqeEmFDIfDK2BKpH+ttTy3I5FtkXCQZ5ahKtmaTMisRAzPPf6oDPUhmBoMhn0dUitFMSila7FuZLr9G4ipjx/cyWI+Z7Va4rxj99hx3rz9OEQpcC/nsw2bjLgs74XAXBpaBRgOhzzzur8pi2+yfZ9SR95Lam0TU5kBrYW0tq6l7nEppny63l5DR6u0uMlCe3VM+a85pq65oBxe3GOoJX+mtaW1FhelgymSxGxU6gpI4jHSUNqFs2l1TCfQhbb96SghP6tdy6qqqZZLYl2Dl4fhAZ+MP4CE9VFy7zbPGZQ5Krdoo/FBtDu6vLKQvku4vFqmLioreUWTABqROolJYWDHohrCmhaDdJ15XlAZg6bj5xFKh6ZpcM4duaYNy+8Li73pxw4C678YI1btvevvT+z/L3lR1XWTdAuIku+T8p9iYKFnZ3bOifaC97R13XtS3TE74+/I7oRCxjJMhb/CFyinkucpC0qWZT0Ni9Yak9qjfSrchRBROvZSATH9Y7SkakJ/T7rEe/fnACFdd8eSmnLOsavbKPqFSEWZHCY9v75Y2yC0OFpo0EGJYtB1tH2zYWodGVyOqYjG2DylYUyfquu8YGsyUSxUpDkNcwmm8l6TRDCVs2wW1xmmkkxv20o7f3ovtCnF3T0TSJhKx9zE1GA4QKd9NW3bRw0+RooNTAlflu71UVxazC/HlLzDlPZHLz6KRXwjMXXNBcUpURxoQiAEmeiVyc2IU1CYHGMTnXRVSdtaCDgFQQvDsE0XKXk6hbKiahYiuO5nLpI3FbPDA9R8hnJSfOwpArQiphxe16HUHE5Z1TkLq6kVDMqSw+DJspxz+/tMRgWDsqAoS2azOU1dMzA20Qm0R4uDweNdQ12vUk0l9sU/Y4T1dPahR2iahrIoGX//3Zx/7+do6jpNOa+Zc7jkXm96AWweM32tqorJD9yH1ormlx/sPyPeaDJ8FKIo1wGWnuKFZJyf/sJvUjd1kjKOVFVF0zR8633fla5XjqeVglQMVUq0HLop2P0Xn+Mt+XGpg9xu+DG+g4+GL9C6QIiau+4RITDXOv5glpNZTQyOg/GPoKv3sbX/CMYY9sa3J0ElxdtP/hT/PnPkdUPbetrGJR106TIpyxJt88RvpESZMLVQ6g4MCnRI4Xh6yWbWCvdZlLpD1TjaEHt9DdL9U5tvnutg+2bDVFFIB9d8MbsMU3leMjQZ3oki4xUx1Sief+IJroSpOjlkZVGS5zmHh4dfNUwVhUgNN436sjFlbcZgOMS2lqqqmM/nNHVDU1dH3iFaKemySgV5Y9aYGo0GFJklRggqMjr/EHYh83RBn2A8FuZx5xwHBwdkNsl3SI84JpMaSbVc9pgyWlMOcpQSvReXMNVFIEcxpb+umLo22zCRZYjUSjEwBm/Ax4hLXsbCt+ggVAxaBZSJfQ97b/LrtCcK8Yg6iukYAhaoW8XCOQ4GBcesxRoRdomdK5J2ErUCY4hac2615KXFIYsY8MYwHo04LEvKsuTCufPceOakKDQGR+s9bQhkoTt/8VWMVnKsBGhCICQvoHPmffCotqVpao7/2LcSQuT8v/0c9WrVG3BHJ37kwll7kFddz6NM2s9+5YsYYzjxo6/j4i8/IIYRO490c78KFWXAKxojA0zdgzSGsizodBbsn7oZ51qe+8CDNMkj7QEDfYEUIm/61u8Rj+6l1IWiFM8/+ZgU++5IxpZZzj79FLfcdQ/WGEZepvLrGvSF98k5WLNu+dw47cwatBmT+chiPpV6TuLyXi2XDEca28vRRpqmZblYonSSeg2Btq2FnDMx7kZr8E2LIlJoMLlJBcO1zkS8/A5+w7dvNkwNh2PKsmS5XFyGKRUCLkSe3foesRsSpqzm2cce61/O6+j4ckxtbW0TQuRwevhVxVRdVRhj2JpMmC8WXxVMPRneistaKr/iTccfk6HFsJZ+2MRUCAVGa57dehvl2S/09R9TZgQfIQZ2Dh5hO7vI6vRrscYwHMlgqa+hauCD7YwfH5zEZpZq45o/6OZsxYjPDc4oFvPDlPISG/ozy0nClJFurathqqlluDPNfX01MHXNBaWjFQlRCwOmNgSi0AaIayP5vNj7S6DixmMHesOQr6rvs5ahmxAhKMmp1rllFRWqDTjXMi4HqMwStcZrRUxT2kEpltWSOgZckHNsmoa2bTDGsFwuubi3h2sbtFHYLEebTIZylITaRiusph9G6gxOznQjBI4RpTVlKe28zrW9F7UZd2/6SSpebvKXPYS4/m7nkXVdWW3binTpJds6fF2nOrq9aLNmFI0xkhe5zG1MtlIKL7EIJwPbPJHJZAutFdbmqXVQnqUxpk9hdBPdUtCDwXBAvarpQnWb2SS4lolmheoKohCVoSiGZEGxmM2J0ffXo0DEe5LBBudQsUXT4n0gBrk/rm0xoQv4JWccvJeGyZQ2UUjNYT1ffY0Xzzdo+2bDVJZdC1OyH5QmL+waU2nheqWYar9JMAXiWGVZxu7ubp/+kuL75g7FTrXSzDtMpWs32qTPJ0wpndKcMBwMqKo1pkxy0L4mmPKSHjebqbAQREk3HeTLwdTLLCjp4SiZci66glqff0zF1XQpMRGH9SYR5UQ2v6G6nGZ62G0UumhVZPjxkHnV0jY1VV0x2N5ClSUxs7RKEZKiWYiRSisBRFQQ6QthrnUsV0teePEsi8Wcra0Jn5rfi80z0KJxvf3u+8isQhM5eP/DhCgdGWvK6JRrTV5HlmUc/5HXsv/+h6g6niCtj4Tb/ZMG0QvY/Nm10i7dqh8j1a8+se6AaZr+xS4f29zf+nf7v24cQymF/w/PoZBi6uCdd1B99Enh6UrG3HmOIQYefuITAORFceQ6tDbJKAPf/an/gD55gueffBxi5DvVGX7j5LP9Z0VsKO9bGYV5OfIfLvxzxu0O+qa/iFDJ6P7UlVLceOs+Z58/mShHFB976edo6wWrWw949RPv6hdCYZx10tKtjXjb3vep4+6ZEaXO2t+Z6yvj9U2Hqe6/SzFVlAOUsShteOHJJxkOix5Ty2WdOoWujanJeMJiuaRtmq8ZpkIMXzVMiVKtJc9yHnTfmhy0K2OqO8aNSXWz27FORfgQY6+LMr7wkPxcKV7IbgIi1SDwzuEOfiT8gWa6xlQM4pBk+eCKmDJWFq0OU9436NiSa8eyTZPzqf26W9iUUimC5SvC1DUXlP/40k18x4mnxVBpySuNiZKTjFolDRLJCSsjw3CklGV3UlEqP0Aq56lute5uc2QwHHF8Z5tX3XYzTz//AucXUw4WMybtLtZqVHDgvKiyB9EzOVwsOFwuqJqa33zhBgajEcvdBVoZPvLEDt9+8RFGoyE3vuoGjPkWkco0mtxAbsS49t73oLCRao3RhvL7bqf51aeSBkQkOMd4MqEsS3yMzGczCdcvMeb+b33ed8OENvO9m59XGxac0gCz6Ywz73kTtmmo3/d5MaDkkb/sdhkO18Hp4sOP9d83RjN8510QI6v7n8C17giwulNViqRuGddT2Z2kMVFkX+laWwOT8Yhw45toUJgLF/BBo4zinTf9ZT4ca7LFLAEhgU9JEXNnss2x3VQw9oG7z/wF2mrGh+t/wB13HuI7xbogMrgvviAMy5M3nORSy+4BcOT+Xl/bA7f/Ve577B9c95hqm4bBaEzXins4m3Jwca/HlC1HfPzgTqy1lNkaU7PZ8gimdOKEuTKmwtcFU8eOnyDPA3Vdf9UwFdp1l520+Uo3lQ/+CKaM0f1uFNIs0KUmdapx9JhSMDr/IGE2Y/fgkNNnTjE/8QaUUrQT0IeCqTIveacecP/VMLW90zdb+JAm5a2iyBSYLGFK7qFPTtnG0nnJff3SMHXNBaUoSz69uA+lFNYY3r79lBRyvJc4KK1WmQY7UGA2DFt14jyQaYVrAq6BGDZXOIWPgWy5QgHt088zMDAqCxZliQ2erHXCQoq0RTbeM2tb5lXF7168nQAMx5GiLLG5EL6NJls84P8YeV3wxN4243FOZjRGS5fFcrWeSAW56RBYfOjRvmjZeffb7341Wmsu/NvPSWEqbV0InP696ha7/3ehfyoCXvZwkkHsdQtJx/eETBZsAuiIMxUv+ebVT6Lflh95rPfiUNJe2XmO3blEpNgYYmI91Zrb7rkvTdYmksmLz6C15sfz7+Z0fopi+jhGG0ZhiUO67kIVCfYYq3ae7nlqCOg9NmkMUIDWkQ++8E9ZzmcsFoFsUpKrRCiY6j933rWQ4x8csjpxrzh26UZcfode7sZ8/beiLCkHQ1H80wbdhusKU2hDXg7JioFgKiswxjAab6ERynuvCj59eDe5FUy1TcsyORbd1mFKecWLpMkAACAASURBVC7D1GAwRGvNdDr9umBqNpt+zTHlXHtFTNnM9DuNUWhSYmrh1YmR+Qim0gJepnrw9ktPYrTh+HLJ4al7iCHwn8bIL14820cZl2HKSGOAUqBDpK5bFsuW5SIw2SkSptT699Pion1I6pFfPqauuaBMtndSikGJxKi14KWnnZA04pTcpNwq5DxlSEl1ZHVRvJfaRelsSUyXID/XMWBo5KHs7TO++QaacWA+mgu7aozoGAlGE42maQLztqVxDpsX2Ey6Gay12LxBGcNwOBAyxizDZgWZtaLGFgNt01DXTbpZkjs8GkqnL0mcxxhh8K2rWm50B3grzKt0OeFkY93K38mtbrr84qHY/jibXlXnLdR11d+ctV2vld8ufZRdwTD4dTNBt3+peXRsANAFsvJ74vEfPQ4btpLSL6nYp1J4blITg95oHy6S8eepF19r3bdet60jNoG2bdJU8MZVpRRNF3IrHfErT90G6lbU+UzqZezua/dfaJree9rE9qWP83rbJjs7bO3s9N06+mB2XWGqGI4EUybl74tCMDUaY0yGtRaT5WRujSlphe0am18JpjTOh/9fYOqoMa4xRYyJCuUophTSKXYlTMXJZI2peA1MqQ1MqUhdNTRtoG4jOzZbYyqsGyZiCIIpt25Q7x/fl4Cpay4ot999T/+SUQTK/adoYiR4GYTrFME0hjxl2brbqxUoeV4oIk4J1fJ6bj+mlbB7ABpX1Zw5fYaibvC1J9Y13mYEa4hGUxM48I4L1QofApOtbUZb26LfHCPlaB8VI+PtXekBt5phbtj9gTtovadpHKvPPc30Aw/LKp6Mo/ze29Fa03zsaUktpCLV7g+/hv1ffpDVaoX3TogNAaU0Z37ijRSJLr+b5O3yp3Vdc/aXPt1rMkToZ122JhO6/OQmfYRzjsPDQxEWovNIJbVhrOXYj7y276DavM8hBGYfeoTZdNpPAHeekLWWYz/6upRDFjPRCOtp09RybU1Dp4jXGY9WmpvvvgetNGH6JCi49Z776Oj4TfKiQDyh8WQkhIKq66WX4TDvPEo1pHfbxrZxrI0FhXTf5fuSHtCJiVe8SZWKumHN37TJA6E2968u+d71sd1+1z3cxt0JF4ELjz5x3WFqvLWNzmT493fP34RaRjxC0ZMFzRDDuDQJUyK5a609gqnuufbpuvRsR6MRi8Xyipg6tnuMoiyugKlIXddc3L/4VcXUZDy+QleieO51U18VU5PJhDxhinTcGAN107BYLI5g6tEHHuDmO+9aE3kG+hZck5Qpj2JKFrpyUFyGqXz+JN556rrhJ/ef5RdGpzcs6yqYYo2pyd5DmJv+ZH/Po7oEU86JKX0FmLrmglKWORHhCDIKRojOwbyu5aTTz7xSLOdyHDF2BTrpPSiIUeGdEJl11R2JqCTnKGJUmiq3tECeW47vbOEODoTw0RoapTh74SL7B4ccTg8pB0OssVitU897i2sqMZboGL/jVjIjXSd7/+4hqroWkZ3b26RjElM7akv1/of6a9ZaMxqPOfWnv5WqWjGbTamqGgV45cmznMFgwO6x4+t2zg0vJ8ZI3jQcDoaASHx28p/WWk6/503pQav0rzxQ5xzlwQEv/etP4bxbe2Yh4D0sPvwoN/yZN4k3lo7XeW6j97yJcn+fg/c/QF2JNyYTxzUX3vtZTvzp11OWA7Is649ZlCWjP/tWVssVh+9/gKquqFYrKTTieeKhB9Fa85N3/nH0UPjJusFQyWvH3lg/kn2Gv6i/vzfgrkQYtRhhtxgcscQuDdJ7Uip9dvMjCoUGlTpRtAg9GWMo8pywsytSum2D60CcaLk7AFxvpZQ3PvdPiIMCie4Uo93rDFOJTj8Gz2+dfRUx1CiEridXkBHAOWYtPaa8cwkLa0xtbh2mdra3qarqqpg6/ZN/rMdU87GnL8FUwSrZ9qWY2j1+nOIdt7OJqfZjz+CcQxvL/sW9K2KqaVsm29spUtEUb7+V+lefksgmeLQ2LJfzyzAVQmB7e5uix5TgMS9LRuMx1XLFcrnoMfXMo48Qidx0x91oLSwEWl0NU5JqtsZuLI5XwhRsYuptWyO0ln3WYzBGbKVcaobnHsDPZiyA8fmHWJ1+newrRsYXHuoxFYPHt23CVItrm74RYH7iPl4Jpq492Ji0hLse6mA0jVIsokf50Cu8GaXJbZ4uTSWvMvQnHVNb3WXBlJL2RsnXw1IpdGZxzlPFwP5qmTwpg9eaVdsm4RxFUQykddFmBBSWSJ7lGA2jMmNQJM8j0WV3HpJN3pNK/DWb+VilZNCuyAtQmtl8TtO0Kd8p4WiW54xGo94LP7Il10lI7TqNlA4UkjcNIUjNIHlK3cvUGCNDVDbrCeS6HYQghlxXFXlRCrlb2qe8QAN5UfSsqnVV97/XtC2L+QznWrK8IM9ztNL9y0cbTZYL9XgMUdIDXV47pR1Q9FP4necjKa902SrRqSeCvpi+1wE4rT3re7Txe5tdQF1n6DqjoZPxqv5++SACSL5tqdtWzlEbTFFiEp1E8L5vXb3e8l/Otf1iSlDXIaYKjBUdIGstmohRUOQZNlGoXIapVAd4eUypV4yp3kxS5Nokh+FqmEKpq2JqNp2+DKaKxFeVKElSKqgocry/Mqbm8zmtc+R5TnYEU6Cugimx5din+K6Eqbjx0v5yMNVhpe+sUx2tfuecJEzFK2MqeN+n44wupK04BGxRvCJMXXNBaeoqnYQc/DcObuHihSF3hbNAxKAxypKrjN+f34UE4tIdFFOPdrfadbn4GLqGSPjOE88QAVFPDsyIKCuCP7O24b1PH5P+a2tQxlLXW9SrFW+aPMpwOCLXJSbLUVFa5f7kq99CZhTq3HNkeYbzgflHnugfTJ5p3vLMKcldqnUOP3/7rRKFacPW1hbaGFrnuPjvHujpm4mgtCLPMrbf/eq+VbBrT+xs3/vAxfc9QNu2KeyVH4QgIWVVrcjyYiPUTy8XpPXWWINqpCe8W6BCjMmzmzHwnqIse0+rSwkYrRl//z3YuqJ672c7xBGcY+99X8BaK0JIP/LaI4sBKIrvvZ3MB0xdoWYzQgy0H3sKIjz3+CPJdiPGWG69+951KgpJAyiERTnq2F/LkdbM5JCkeOyokfXXnzzcDZR0z6gDUwjCLeS9p6krVsMVWmtpWc7zPm0WUgt5p49+PW1NXdG9MLxSNBEqIvMgqoybmNJl3r8QjEmY8oGQlBK759INtK3v4tUx9cJijjZGOLWM5bfO3UK9WtHUNcfzkxybnSF3Q0JUFIUn05HMKApriErhfKBJcg8dpoB+MTnibCRMTSYTtLG0zjOfz6+IqcFgwOqjj/ep2f6alAzbzmfza2Cqwn/oUbRS5G+/DaUUTSt51leOqYLqgw+vCR9j7GdYus8CvX3NZjNWqxV5njMcj/uaYu/Fa43NcvIgddsAvPDU49x0x11ASGSOIgHQ0fd3962TArg2puAnD54lhMCFm+/m/v2p3Ms8484NTI3OP8hBb32CqfH5h8R2UqPLJqa6Wo6MAWQ9pranTzDdvedlMXXtCKVtaV0QGgA0dePxgVSQCiJApTSfmN3D9rFtULpfRJxzhOBwCprg8FEGndaDdZGPnD1DJPIdJ57GxpawKkXwp3X8+tkbce4ZbCYa1ybL2Rlvo7ThRXUn5xFZXath8s7bGObyMLwPXFysaP+NMPxqLb3jHXle8Y7bkl1E6tQiXP3qU1hrOfETb8Ray2K55Px7P5f4cugfokKxWC555l/8fmdbdB6jSiGreCR170X04WEE1zqe+ee/l3LLnZGsHzaoROng+x9sFgUvvPdzvUjWEVcN1S9unedytINF6FLa1jH/hd/fCFlj771seh5dAX78/XfQprqS/Z6bmX/4CR753GfF6IzmR+/4dnSuybJOEGkjoonddG3E2DzRO6xlWHuaFbUGSYzdUJx4c73HGzvakS6frbFZxmTvi73nuX/83v5qOw4lnRl0kV/LxL/u29991Z/lzb//MXyA7zjx7FUxZcuScrKVMCU1FuccQTucTphykYDHx66DCTp7xHMZpmrnhM5dabRRfPzwLnaOD1BJV8MqiRashsIqhsnLDj4wmy9FfprLMdU/w9jNYYgdWWPY3d1NaoxLDg4Pr4qpJqXJvhxMnX3xxTWmfv6ZLwlT08NDZrPpV4ap+eIVY+rsM090QRevuu0OmrahrkKPqTzPkmDZy2HKpvqO4/gzD/Oe1Hr9y6fv3MAUG5iKrwhT3jlhX182PSsFKdrL2y+Ig2++TD2UEJKXqCMgdAzGGDQyOCP5fy3eR9MSIfVhy1Rq8A4fhFit0zGQCCVRTRuNTSEjUbzc6XSGC57gB0y2tjBZjrEZ2li0scL/rzW5UYzeeSvWGDId8S6wuv/JPhSXm9alPzydNTUffKSPChQSrm+/+9UURYHSmpf+zWdp6jqJ+xxNakWk06TTMDgS+MW44V2tDTay8TXGDZXHo576Zr74slTakcNEhJ10My2wjkL71ssj502fOkhRd3+Mvt7QOVdapecYmX7w8eR1ioy0MZrye28jhkh1/5M899ijkJ7jna9+jXRlpTBaJqWTdoXqCpCggsarpKOyUXxNWYD+pdRdXaT7WeJgUhptwER5oekQCMawe/hEAn9kcfLVtM6hnEJpx/W0/fjF53g2YeoTF2+mrhoOD3a4eHHMW3Yf6zH1+xfvoFyNeky9eftxnEuY8puY8uuoX0lh1+a5kCJehinPF+rXYkKOCRmD8nJMZRasjj2mfAgvi6l+UdnA1GAwSJhS7B8c/BGmEExVtesx9cxjj/X2HtO814133JXYO0TX5eqYku4wlNRaRBMG3nP4PMeeSp1c3QKaUsFfKqY2GcqJIramlE9kllfeXmZB6SRn0wNVqW1OW7xv+rxljJ0HEdLNaEQh0HtCFOOLabmU6VCbhoEseVGQpZWxdS2Hh4eIWE5JMRylxUSo1o2WBU0GFDVWg4oe14ougGgly2q/9jjWKam18YBSEZSEdkWRY62lbhpWq5UYaPKELjPDELhSwBc2DP7IkNYlO9js1d/I7sj/jvz90u2oscbLf9SDb/3DeOT43fX0t6P/mfSwR9UV+5PxRlHa00r14lpaKaIBbdS67TDlgmOMxNS5AvQhtUopHpX25VHJYzO9bXXhfD+XcIV70AMAlegsunZjfSRVobSGLiV59ffIN2TbzEMfwVTf+nplTNXlSoSxgtAEhW46m9TVY0zf9ZSXhaSBLsNUfFlMaRWOYKpjnf3SMVVgraX5I0xdFVM6yXJ3mEIptO7u58thao2n2C3m6sqY6p/VV4CpGCL4tMBfQ2Hr2uSQreT+QgqbOqW0T83uZj49TFGGoShWhLBcRyGs8/vdg1LIZ/MipywL8sSJY6xlWAxYLpesqhUvvvQSZTkgcpxsOJZpUoQZs7CG3CrG77oNrQ2zDz5O3UgOVSQsdQrJDNaYjRSXov3Y00CieE+FJ601x3/sdSigbmpe/FefSpEXCdQbT2HzYWz+OSZ+pkDvpfWm2TsFm9nt9KOjbtoV7T1u7Gbzw5d9P30jHvnrUQtX6Ryu7KnFfsHvMZz+EIJIIi8+/ATGyu8bo8mzjOxttxBiZPXRJ3jiwS/IURKD8a333rsGeheud5xiwWFMlsL69ogHKVoNsffIOsRe6mX2tacYj9xZpRSTvYe7G3/kxXc9bL5tpBZwCaaKsuD3Ltx2VUz9xuzElTGl9VFM6QzTWGaLOcvFkrZteSQWMkxpj5MNR1fEVJHJvqo6UL0MprqOPJVs+1JMTbYmKBRN03Bhb++PMHUVTCkFxkqkIXT/hnPPPk2IkRtuvX2j3iaYMtZsYEra/31Y19VMlpFlG3NbPabCmtzxy8SUMmKX3b6vtl17QYnSdRAShbFvPUoZyuGYQZFj33YzXeNF/atPoYjkb7+FGAP1/U9KETXIBWil0wSnFK/a1ouSm1L8x/2bCMHz7See5rfO3shgMGQwFLI5oyNGQ6EV43fdAUoTUz2nTd6ezWzPS9PVaVwrN6f6wMN9zl4pjdKQZzllWbL7w5Km2XvfF1guhbremk5BzafWQd3n+3tTihumnELJ9ZzTUUMU3rnOu9dHxL0ufTiXDu91aYvuBTIYDMiLgsH33cVL//oPegXGyyJytel5pX1f6o11X8Oln5APHcVmhKhwbWT+QckBa6MxKQ2SWcvw+25ndf9TeBdo6opHPvsZIoqb7ryLn6rP45MypnOSDtWNwtaW1fa2TPVqGfJqXdt73yEE0U7vPM3k2ffefbwEDEfu4YbXeh1tHo0ohl4ZUyKEJNUF8TK7iMCntMgrw5R3gSyTQUSXeJ0GRXkZpvKs04DXVK8QU0e68/6QYMqk9uJvBKZkXstLCcBKjeOlZ54ixsANt92J94KpWIldAAwGJXmWbWDK9CSUq+XyEky5vnvra42pay4oyZb7lV5rjUXyrRpDNhgSo0QwdjgEBcV4DDGQTyb9zyK6n7hXat2rkDKwvQHs7MwYTIdSbE+8W9akiWItHSbee1wIBC8PQnK7ouOs0oMKqZW2W5G7Ap9SIvaUFwVFWWCzjNZJv3lRSEuteFtCMhmqFSHEnhFj0+W52hodL/lT98yAPl9JJ+LTfzQZW1et6+5RRK4jHboj2yuKnHIwSHMj/rIjX+nkjnpYR793Ra+sN6zurq7Bo9J5uVZo1n0IZJDyuooYtVBvpOeglUJZg44iF+BtooVInTERIUbs6Osh5eX7y4n9GbxcvLGZGrneohNALiBcHVPrwvbaEVd0QI9fMqaUUpTJtl8JpvoOpz/C1NEz+jphihj7Ar5WV8ZUSI7c9Yipl1lQwjqwVAqVqBoArMrgP55LJ6coRmMx/t/ZAyKDre0UlgmBnYBjfWLr8tDa23nIHWcwkhtojWbyzltTj7shRM3BBx5ONNSOI7QdKXdcfu9tAKw++mRfvAobeUCQzpOtH7xXCoZKsfjI40IcmWVorWnblrZ1NLqWeRKfmEGNThTal91u+kdy5Xi6u5l00pkhIaJ/oHHt3Vwat/cGqlTfNqm1ZueHX8P5X/pMooc4ehpXPoW4/rpxrCPe3MY1bGJFbbygum/HGFh8+Ine4EPSmFFaM3rXbckrDjz/kUeFMjv97k133EXMOjlb1c8iAJKbTUjXnelvnPalV3KpoXe1h82p++tui4FO9fCKmOpfmirRkKyxYjo10i8BU1000GGqsJBZSWP5qFnW1TUx1Xm9vYLfVTBVliV5XtB+7BkWq+qbElPD0Zi2ab+hmAphvYhYq3n+icfSbYicufV2PIHoA0aLDRgSk8Q1MRW/bpi65oJiSCygir6IullcXX+VF0mXJ+1uGdDTTncPeFMGNvQPfQMUqqM4MCiTg5bBxbptyN9xGznQ/n/tfVmzHcdx5pfdZz93wUaAlEiaC7h4JNIQ5ZH1MI+WRUm0aYo0ZUv2v/BP8H+Y8JMdfrA03BdIXEa2NH4YhyMYogRTIkVhoQhzEUFc3OVsvVX6obas7j4HFySIewB0RQC3T3ctWVX5dX1VnZX143dNHtpNdNxuoRW3wP/2AcBAq902DCxC7+t3gJkxfeUUCIRDj96PdruLQilsH39bp48iUGSXGMjJ4ZiEnRISQELW8tppnc4HqswK0+lEKHp9GssyQYQo9tNOpbR31vQHr+GWv/kqJitDTMakd/ISxMuFHY2rl0ms6857ZhlouQ7iFxm5soyxdfyUXk5pEdoEqJ+eBRhYe+goikJh8vJpFIXC2ZN613BEhFvvvse9+EDmJSBAmeW5My2myDBNtmaUoWI7dx1GJhK/lynEKNAitaeY4qiNwmAKpE2FO8bNehlTVgEoKhym4jjWM1Rj6Xno0fvB/+8DbcU0S65OTCUJjtx0E/IsXRpMZblymIrjCB++e1rnoxRuuu0O5LkmbYU4J4hi2lNMLRxQ+sZFhGxTy5gie+61bQXHj3yr+kHbT6WVuJYjthWaFcAq0j5rnnvTlSPNBu00ttfrod/v49C373dWWpPpFB8/dQK5AVH+w7dxw6PHsPbYA4jiCPlPzmKSant8hgY1g8GF/sCVpInef5NlDlyI5ig8+99BQzNc53jlkQBngMmAqRQcm6mnRkVRaD9cz76BtYfuRS9N8bsnXodSdhewydH2CYcf2FiAmwjw2xfYpbcvOEiWh/Djo+xnXY42i1QpIz9+ClGk27ZNxjy8pTdu9R+8FbNXTkMpxm9//RZuueueYKfw493/hTzOvBdUW4iy7VxqEAtQscRj+8Oyq2UK/V4XvV537zCVFbvC1NraGlqtNpI0wXQ6xXRz22EqjmPc8Ogx578r/8lZ5Hlx1WNqvLOzvJgi5TAVRYT33zmNz912hx7gW+wMPIq80EuKAlODfh+5+Sb2WWNq4YAyGPR9Y4qpnFuzlYO3UQQGG7MywQLMKKgXf63NvKmJG0XhDqaR5mq6cmaWBG/v3opj7V+o3dFnEUBPy/Nc2+kDet+EZVStlv5INc1y7ZjOnCZnR11mRpHnSDN9XK7KtWUKIlO+VFMH7hpG5LSMETZSKZRpSim5vBG8UFh7UJ1MJugbdtnt9TCdjIViyBcLO4WvFuA70ANUKDjLJ/6N5gAfCinaQi9FEANFwW4tOIrN2nBkP9Iy8jwzH3a1Y8EojtCitlFe6+dLyub10Ck2V5W+fL0sYTDoG1zhqsFU1mDKSrYUmGJGgCltGUVQ5nRTVsWeYWrhgLJvfT1oNDvq2umV+y1YkoKtlGdNhdnQqBQjUt4OXxl3LPa5roSdaZIvl2zjMmAaaWVlBb1eH1EcY+O5NzAaj5HMZkhS7RLbuoUefvMuMCukSYq8KLBx/ry20VdmLZu88ishG8BmV2kUqgR7ZeI5iiSiCuWpmhdWGBOXn8u2NzJBd+poZweryRTdbh+H/+IY3v2n/w97fjQbKyDf7yEAyClPRWTHVAOmVJYoEDtEP2lihbxgoFDIf3gKcUzoP3g7AGDy8ikYogRm4Mxbb7nktx69R1u5mBdWFNtDveBs3y3APUMPZZMMatkGEwBY37cPo/U1/WMJMbX20L2I4xijV89c95j68P33jDuY5cIUAYhjwtmTJwGC2RjKhlAXOPJ7t4H1EW3aA8IVxNTCAWVnNA4qX57q2NEqjmMc+PMvGjPFdmU6bjdIMgOqKPQ0ThXI8gybz/8KyWxmPADrSjKxUc5Q+G63i9W1NRx57BhWVlZRKH2mwgdP/Aw7O9tgtyu7hc/91R9iMBig2+1pfzfPnMDOzg5GO9uuwfzu3lIwozeZ1maEiqhRasd3Lie8aKhOGQUrc8KVsRAqpFIK5546geFwiJv+6n9idW0dO9tbmEzG2rmg8aBaR9q45tq+zMi+gWAVqZwiDBbUXikhmoH0UbBZgeSFt41OKKe0+l0WuXra7yu27NvuvhdxKzYWL+T0wa4RB0s+FhymDX29liu89YufY7eYWllZQbutN93q9tLtZ08/tC8Bt9yhCmR5jokZCD4NppKvHsL2sx9c95hK49bSYopTrsXU+2dOuXoyMz5/51FXdiuOP1NMLRxQrBvquvoTEdqdNjrtDtYeuge9Xk87nYtiY2NvN2GpYLoEEPIiRZbl2D7+FpJZYlxLs6uUFdpN7Y0N5co3jmK4ugYQIc0ybB//NWbTCabTiWPnESKsfOtuc2JZhLwoMJvOMJlM9WYtVyNrWofgw6D8P2RQvkPDh1K9bO5VQDCU7+RyY9oGlmSl8qIJE5BhJkmaYOuFX2Hfw19A9vTrSNMUeZYa77Ts3CSQyMB69S1rBrmH8plvKyufny6LbMgovlFEu4/CKzuLPHyb2em3BY3dsRtHET54RwODCLjlzrvcurAzlTX5kmHxbOqpggZbriFlt5iyJ/ZFsfbk6zGl247IDigAUCAvtLuO2Wz6qTA1m80wnU6x9eKbAabsXg2Lqe0X37rmMTX449sxHvSveky9f+aUwxQR4fN33KUHDOCyY2qx2TD8yO/+QiuKPpOii36vh5VVvaNdV1jHYhFXMwOdXpkT3mazKcbjMdIkNRYtplIgN5qD9clyMAfSdbv6QKsszZCl+vCcZDZFkiRuTZGiSFusMGuTwCTFzmiEyWSCNE31WRICYBCKH9Q7/E/QDtvdofaUCZKcNlrWVZ5KlslS3Y+6F4/VH6UU0jTFaLSDm3pd9PsDpEmKnSx1SmEBDni9dqKzXWYRD9ylVU6rVLpQo8JzVcoxJcuezc7eMr/RXWBzsh8tYdiwdgWilF7b9oxcGVDLjXXsWL0yYKNiPvtbhrAbTA1WhgZTWIApfV8xI81SzGazT42p0Xg0B1OdAFPbOzsNpnB1YioiCGvAy4uphQPKrX/9VVgWpJRy4I5IHxLTamnGopiRGX9dzu7ZBoqgj8bU0/ELz72BnZ1tY/9dIG5FDiC+AfXab6vVwg2P3Y9Bf+hOVpvOElzYvIALz//SNKVuuFarrW3hux2kP34HiVH+yWSi3VuAnHO7Ei2osJsKGAKWY6awLp19Odi0Mh07ZZG5l/OthrpJdSmJYSF5XmBrawsrO9tY/7Pfxz6KcOYf/k0zYa2FtTkFYBXFVTFoldlcW31g5WLbdXv5QW836kdmyk1mbX71W3fpTVzG+WTna7/nlgjOvXQSaZo7tyw333W325zn9loQgZlgj2d1H6GXKNx4440AYF4Meue2noWRwVTbAdnuWnf7cwDADA7MhflgnmE8Gl0Sptb3rWPQ12fvdNbXMZ0l+N1TP8d4PDIlVDGlFGM0HiPLUmy+8OZ1ganOsycwGAwwGA71Ev1ViKlut+Mwpc+NATY+PAtW+myew7fcrr1IM7tvaZ8GUwsHlA+ffN03ghtWAaII2+aULyLSp6XZ0Q1k1oD1x58oijFLEmwffxOz2QypcUMdG2d2bm3RtzXsUZtHHv+SPvek3QFRhIk5pnT80kkxjddmqTd+5wFzKmEHbAjEGwAAGtRJREFUAGNq2Nr4ydfhdxIb+THfW6atrugip68UDJSWkEh2IDKwx2tKpgIA7Gw7wjTwIPT52g1woljHaqwYWhk/fuYEDj36BxgMhjjynT/ER0/8DFmWhqTPAZT8dJpcRpql2KUIt54KwC6TwPpY0uv15SpL6ldWOffBGRzoiWfOhPFLp9Ay52z3H7wdYMb0ld8CYAy+cScGAKYvn0aeF3jv5G80UwTh5qN6Oczv44gcW1yu4QTYuHBBX9RgapZk/lhYu1RFUQ2mIiRJguls+qkxtXn8TUxH+qwRiane12/HoUM3BJjaOv4W0vHYsddrHVPb29sAEYaDIfYfPITNjY2rDlNZloOVObu+pZfstCMARqvVwsYHZ7WnhLxAnqtdYersqd9gXlg4oEwnUyM52Sbz16RHLSJCNtqBN0ezI5w/V3qWzDCdTJGmCYoir1Rcqj8RodVuod/rod/TLAqk3Q7MZjOTR+HSRHGEXq+HQX/g1nntKW6FcaEwbyrpeqk8bS1NJV2oyciuVVp5WNMtp2Bw92U24fQ+XAetmcpKRkbij2AtaZIgTabotNsYDAbo9XqwSxTzQsVig4wVql2fde42PFC0t1MVehy1+uv+E/cFU7P649aLSy8+VTByKMSI/M57E9ce5BWLsxisF1xm4zbELM9Exr+UZdrLFHaLqSiiGkxFzlnjLJkhcXj45JhKZgnSNL0ETCmR/5xwTWFqhk67jeFggNlkclVjykR1cf31pWLqE7qvT1PfcLaDggqaSo+eOREAQ1/6EVMeqkUw7pJFb7JQOIoI3W4XBx+5D0QRsiyHUim2j7+FjY0N49yNXeO0W20cfvQYOp0eiCIUhcIsSfDx0ycwm021zJKqUVW5gg6THQWr1RQ+F2DhIFkNdXElEXzJXBtn3j0hekUU2w5KFdh6/k2kgwFu/t4fYbiyAoCQ59uQNUblVwgCrUjWK3DhnOURIrN/QIcomrfByd8L1u5LQXe541cO4EWuz+HIjp9EuxVh+I07XVmTl08BDLTiCCvfvB2Tl88gzxXeP31Kn6BpSr/16D1uv0S0QPn3IuwWU+7yMmJqdXUtwNR0NsP58+drMbVvfX8FU9tb29cdpqbjCcDA4SM3XvWYoki73Wm3W64se6xAK47Q6UTIcxVg6vN33gUuCmPlpjG1yH09LVoP+9vvPs6uuoGi192DHinDO2GzBL0o8xLKSBBTLP/UHSxjorEyh3RFkWFc9gRAuM2N9ZYfc38GoSK9pU27SCsphFwDrapdWR6uzVj2kdQl+bHWNmsURegPh2CllSVJtBtyLuUX/FbmnjnXxLJRV5SZKkRRrMtjuCOdYddU7RKNY8qiHViWrYLuFtoUsjuhYkSEVosw/OYdOkfFGL98Ct0/uQ1E+oyW8Utn3LS9UOwY7s1H78Lf/e+/X5p5ytWCqcGDR5H+y7sNpnBtY6rdiR2mMnNIl50hZ5mqxRQI+MdX/7UWUxe38oL3YBpIVYkHvVZI0PSFZDrDMkoNYqeyq9+6G51OB+1WG+4DlVLYfP5XeoOWZVq6hUAE9AY955OGoTuvyAtzKM18N8tBt3PIfxauj3CJCZUZpdSmOdnUK75kH3PikABTJZ5cSdXrsbPp1IjMJm3krFMUM7hgaJNLo8hyOm6Yb6D4JnN9Jrct3TeAtiaKAuFJ6kug05Hvg1KFrVl53f08F67zCej9ye2uu2avvoOIgME37jCDzWkUua7Tf518u65F9zRcCUxZT79lTE3G411hqtVuoYijBlO4tjFlqxMR3LIyAGcN1mrp73JZUThMfeKP8q5w1wZkfpvGKXkKlVzDdkm128KKRVGEfr+P4WAF3V5XDwxFgSzLsRWR6VFoR2YA3Kav4YreaAToY0qzHFM1RaFyFy8Mpd9ikLeS0aLoAf2oXgcgcko3L8zvkJC0sf6QWBVdl0a+EnYJghnI8syJ4KwzYJS88LupFXsrIsfkrMWOkcP1uwG/ZMt2NcayWrYvNGah/GEqy8ykVvhpOrTWuCR+nbwotF5Ekd4l3LWqxHqdmCJob7xxhE4rRoYCSmlfSMsYrgymhuj2etBWlgpZlmE6newKU/FgCHS6DaauI0y1W97HW4gpLdduMLWrAQWwI52vlBOXwgZxT9hWxaSp0cWYInzuO1/Gyuoaet2+rgz0ATHT2cicQe0Vn8HodroYrqzg5u/9ke5Y0iP3e99/DWmaQi4QVBlOPQXS/bFIWaVShkN92LQmD2ekLh9ZFw/VvOvdGgho1qSxp7GGOAwjKsUAF17ZzQdBK6pbZbXXc5mH4G5kPeRGpkR27EsyMGdoIgBhfwf1cEqu45SMflDm8oVR6OzF0+ZcD8LAunV55Yz7mL/+p0fBDMxePTOnTnsfPitMHTp4CAceua+Cqe2nfzEXU/v//Is4cuSIw1T243dR9PoNpq4nTOWFw1SrpQfNvFAOU/2enu2qTzqgHP6LY776zEJyLVb6f9/xo7QBhzSLs1NtP7WFxktE6HY62P/wF7C6uoY4bqFQ+oPVx8+cwGQywWQ81t4+iVzbD/p9rKys4uAj9+lKkvZZlCQJtre3kKZJZc0wZAlixIZRNnE/CDWEqLTkK1rC1NHGN24x7Jvh4nshQkDZ7vatJpmHKcJY28AoV8CKfHUd4XK/SSqa6VOW/aYrSpE+b9x+CAa8aWK46Ey+fE8nxf+6Lq5fyK4RW/on4tg0AjguQg271QyLkR8/jSgm9L9+G6w56/SVM7Uvmr0O+/bvd9d1mLJY+aSYGg6HOPjI/QGmtra3MZ2MsbO1VcHUvj+9F8OVVaytrgWY2hmNGkxdz5jKgcgOLrH+jlYodVFMLRxQlJJeJr2I1tSMzNnUQqRAYHsddr62p+90uuh2e6Ao1lv8VYGiyJGZ9do4jrXdtC2VgP5gKOzidQWzNMNoNEKaJMbd9PzApb+BDXzdlJrrLqstSqW7QdxyoTZBXS5uClyVw6k1W3Htb7+uaYFu7+vodYV5nz3uxcVGLOuCIYqc8rtUki5J4UhvPiRZV0ug3RujrOhcaRIWZZRb2ZDzIHg7fkIMDQS9DYOEvItZ8pUOF8NUdeJxqZjqVzCVXwRT/VpM7TSYajAFI747jvlimFo4oHz89H/C+oWxIyIZp2J2nwnZQ3ciu+mK0Pnj25zLByJC9i+/1fcIZr225RytpaneUMXMyIscwwfvxEBYLeiPYDrdysqqPvTH8KE8zzGdTfHREz/T5m+2rW2VS1rpJuUWlLKyRBoMorPdc652lEyHksqGylcNZeUms3RgsejL9X+8ovp20URITLnhn/mXloLrO2PAYDdaqcCrgXEt7zbWRfOXLIxis9DWyCi5JNx2HbjIc2OLr0rZhGwzcJxX13A1ALBtnRfAzo/0R/s4Iqx8U5sb/3Tzjvo67FHY3tr+RJgCSGBKDpo6j1aszyYBRRj96Dfofu12MDMmr5wEZylazNi3T3sPt5iKKML6+r5aTG1ubDSYEuF6xVReKIepTtucW7+Ao11khpLX1NuDodq9pluf+NhcicK//5FRSD19shUn9xsmPjnFJcnYiPAxeTO6ONb28ZqBCdt+20AXWb8tB8tOdNIyR5Q1rMubQMGZ1lbo+k60yhlASrIjsGBJcCxJFq29NLCX1ym7TlcYH/H6ubV3J19P0h9iI7JtTs5BnK+3gLOjcgK6clHX/A4WFdgAjCKtLfaEOMfA2Cs0+xLZ6VjYZnVBvt8I+s2XF8DmiydBBHwpOgngb2vT7kX4xJiymClNYeZi6h/evSimOl+7DdP333eYKn5ytsFUg6m5mMoLbVZsj4WuC7v+KO+V0wjjpoKSArCzjLBNJKdI2vLRpDD5+PVEF1ngRVwZVicG6+CkukBh69upVBkqsSSvYK4M20E1LWGvZEdXBOCgqCDYfJWYulY/ooXXOp14oQgmFwCJjCMM02AUhS8lcg1pD9wRNZIvK8fcwrpXW8SDhB3VkvUUbAmeiWnQeu+0du1YQM4VLmf5tqRykHcsrhZtwtrrsNeYyn70mwZTaDB1OTG1cEAJWUU4qdSyGmsT5rK1oxPF2bCUn9dVgsM7FmDWLl678dYuVay1CojCzivXAX7AFsVWhZHy2I5hDlOZvQBlJbAf4ly3iZeC1FMOqmoU3izv+XVX9gmkhA6RJp1TMK9pbpoLwC56GvLpXyyOOcH99mXYPjP/G4UMgkR8JTguJF6KdWpKErdBClmaXZopZ8DlCwqjkHg+h4TtWWgw1WDqWsbUrmcodcFa1IDsSXOhiHY09DJqFxH22gloQWRjCk2N4xi9Xg83f/craHe7mEwmOPf0CexsbVYbIQgcPOLKkzlBVKSaRls5BLLLOrKXPwQ1BfkE5xkUpTrXihS+IMrqJNvBmpa6F459OZBfe48oMnJUFbSuTcvAXRhMZMtEgzYsZ0Klv+IHEYHsmTqmMlpDbKNb5ucBb7tuycaQSwpXElOHDx9Gu9vDZDLB1tZWg6m6+jSYuiRM7cLKy4nuR2RbSSGwbexQ1Ss1EyOofKKvInsWte4aREQ4+O0vYmVlDf3hEJPJFJPJBNPJGG5duFqCLkas38q45mFYvnjodt6LR+yTVQf3MlsgX3u/VqtEHj53giY97pk8IU0phGy2qjzl3+GH2sgxKW9eKBRoTnDvHbeWK+q7AKAyij9siDxP8uoTvlpc5Um0E7m20OlDmSvL7UZGCmQ1NV2y0WWZMLW2vo7NF95sMLXgd4OpS8PURWYoDGah2KYCVnHq2iL8hFSOVE5RzUGm7fX6GAxW0Ov1oAqF8XiM2XSKIs/rgSXSlvmG5Gtl5uAdmNbJE17oRmYXP1TqSsEaHBWldQQhpCol2lKdsAphREW8nx+r+OTuLdpcJoGsr2XcstZzfcIa0YjIr+0T/Hquees5DbGsCAgz5FJZAKi0NGLj2PVlKr+Eds2prnRoMNVgqhyz+rMs2tWCqcUDStBLIs8KQfIj3+IgRkTYyvg7yjhGAzSzuuGxY1gZriCKY4zGY3z05OvukBuKorCrpHKi1KS2wR3TCZumjjn5nKojsozvy/dKzmyZ0Hz2UqfW+sUi3zIsItV0LekSnKJbe/caWeeHmhilW5aR2oeBzsr4AozuRcMKQVfbarFcE7bpooBt2gQE3w7hx8w6QUO5dkEAr2zYY0yt79vnMHXh+V9i88KFBlPyV4OpGkFDuRZp5C6/oQhFgBVcdCpbC6zdI9jzG5iB2wCICL1eD6urq1hbX0eRK4xHI7z3z/+hD7cBKh3sczSZOYuL3QWf1/xE1hUCQyt5kRfuKE4A7jQ0In12MyLtRkGJ/N30WZbEsv7lrUkwvW2A5AQlnb2c7wq24oFh43Bt1eyHWYDASiFL83KDlGQpP6wqqm0fp9CoKdrIRExmL59GhFKqjtC6fGGtccxLIXwp1fLBJQ5XHlMHH/ki9h84hOnLpzGdTXHuo981mGowdVkxtXBAsVNzO9VyglgBpGimA0hSltpMA1nFLd1gwwePotcfoL+6itl0hs0X38JsOkGWppAcRLMkLmUbjs6VYsv3PXar6dziLrsOZdjdsMr48gmn3sbWI2BKZcYFMNh7eJjTOKI9YQFD7hwcEv9rfZSO48p1ruV+5hZh/8NfQKvdBjNj87lfYTqdgo2b7VCtS4B1Lzqqajj7YsvKLPuBwYgcGyzZ0Nv4tQu2RtFN5m7zK8sWxHwd3MOwF5hqt9potTpQP/0A2+3zmEynDabw2WFqOFxxmJqMxtcVpj6ZlVdlPa48qsu4Mp5gTeytUywL0GwkAkAocoVROsZoZxtJkqBQhTnPwfAwsb5HVqbyB7eaqwpZqbnnHyjHdJziMgd22G79266zWqUU4shZNrM5O5p9BvXs0IBJfBT0YPBLBg4IFKasR3qJWRGj3W6jPxiCiJAOh8jSFLkENZfyELej8EmVCdZIEUhG4l+FGZVyqGQt31gVaoWqIi55uAKYynOFJB1hMh43mMJni6nBYAC7N+V6wtTifShRuZC6vBcUInWucrylQIoYAnd++DZ2RDxvBy5GW7A+mrJUTL2kdb/Y9aN0/hZWj4Sc/g+BQLE+JjXElFHIWlZRMvVTlp2xdxYXOTWG1wgpz9wqLWSugSVHkFyD+NxTv8CRxx/AYDDE4ceOIf/Ba5hMJkhms1Ls6q96DncRmSBeGCAoBYAL8ay88c0gQ75JKgXJlygHZSxb2AtMJUmiHahubTaYCuSZW6VPhamtzU1EUYzBYHDdYWrxgCJrIE1R6p7DyhYK7jFCgmLYEVDH114tWyBzLCUr7+bAVq8ulMlbhT+4D3rsFMH56ZnTMhSFw3tAHMuAFy6162bBYVN4y54YcU15Npq0nKnJFFzLqsL6c/ht1t2t2rikaYrzz/4npmZAueHRP8DOaAcfP30CaZKI0g2bI2GlhFIzklQ+sUZrZA6rINa2RWald4etjbgiuI1okIou9StMtUyhwdT1gamdnW0URYE+EdbX9yGKYyilrnlMXcKSF/k+d7ohP2oJodmOlWElfGTfMK12C71uD+1OB3EcI0lmSNMMRZIEI3hZye36M1O9tgUbjKziK2jFh+gg2V6iBA4Fd9lTWKPgl8SG++7Hvt72+xdFvh3KJojyI6NUhnIb6LzNh1uWsUKZrRB1WLdsMk0SRFGENEsRt9vo9froDwb6gy2biltFDt8Nc4PbPFWOO+86uFcCRl280n0LAGk+eTE2tfehwdT1gKlWu4Ver4csy655TC0eUETHyI7VIxqVo9QqQc2Aqf+atun3+7jh0WMYDoegKMKHT7wOpUZIzEheDkbljXL50ds+9GuzuhAO7gMQ3jm919dSReaUWmlQcv+FSksiHYX1rsRfUC5RyJgqABCiB0sDkqAt0gDWZaRpBmbGeDzC2vp+dLtdHPz2fRj/07+jKArXxlxqgPAFUUvfSg3CKMfWNaxquL9jFbqkSDKWfWSXkzhkmUsVrjCmsn89i42NjQZTQr4riakLz/8Shx49hpZSwI9+jfFodE1j6tI/ypd6wJGGQPMpiFP2ocrMaLda6A8GuOV7X0Hc6oAZOPfUCVzY2ECeZ5VODpWYvXmhEUAuC0TW5w6MTkfwNtrGRUK1XuxZkEldWWJ0wKlXXG1YQT4KeyYj+FOQVgKQA0XyqCFiKEat4suybcpyFl6BbF+xS2RZW57n+PD//Aztv/4qut0u+v0+bvzLL+Pckz8Xa78yc5NrWW8rb7kFQi+oByDXfecVYn+Kt4PLJwTGUofPEFObm1sNpmSlzOWVwtTG+fNov/BLdLs99Pt9HDh0CFsXLlyzmLqI2XA4+pGVTphYBKeXiQ6X6432EUF7Am23W+j1+jjwyH2IohbyLEeSptje2kKR52Bjf+5mhWAzQrI7clMxGwsVr1C+mdjLCvgPdnYtMqIgjRTU64zLxTaGKCEMtsMic44FQ5/+Zv0pCZ5V0knyWZPvMBZ+inRzW8NJUX6pU1k+Q5X51ErOvo7MQJEX2Hj2DQxXhtj38BfQ7+ulLwYjmc5EW5fbu66EstZx6W79koGM7T4mEkCIUDn7wTVFmVVbjkZ13bWn4UphavLSyQZTS4Kp0c4IzIzBcIh+v480Sa5ZTC0eUMpWJGRMCw0AZJf4mjEqimPkIehDYywD7vf7UEphOpthOplgMhmbj3tmjZY5uLZnOCvbCBEQ1Z5yZ8o0i7nM7NxygxkxxX4EhrcGkX5/NMtgAWhJDwU3CgrW8dwth3oJorDBnOIHLrRlPPOjtoKlDEkkXaRZpv/Y1tHEZzCm0wniVow8y9But9EzfZQmiYlaotNB3b1gXo7wBVq+CqpTZmKVeOT/CFkCB92VeflyjShXClOz2cz4vmsw5bLZY0x1Ot1rHlO7nqEE004fw7OriwSriP1+Dzc+/oA7/ndnNMJHT/4c49HIHDfqG87bp+v87cYnwDAXcThX2WW0lYjdNF40vThxzeZFRMhrDj8K60wB0MrT6qKQO30NkLjaPpW+NYpnNyNRuY3nhMrUWIg775kV2CtyWFaaJBgTgZ45gSPf+TL2P/w/MJglyH7wGqaTCUw31hQIVI4gLRG6skgkbpQcdNdXyuVgdjWbFKwsh+ZqIUsWPitMHTxwEJ1uD8VP/gubozE2L1xoMLVsmAKw/+AhDIdDtOIYWZpec5i6yEd5/R9ZMhHQBFSmRV4pBMsyDa0tHbq4+btfQavVhlKMZJbggx+8htlMO6cL2IBdDxUmgLGYzho9cc/KI7f+6RmYk5EsvOCIQVF49wQXazsjVbi2G6Tg4E4t7ygzMFmoW+cIc3aqYRXKgtBOYQWL47IqiTQVcVFpNqRJim21jZXRGN1eF612G4cf/xI++P5ryLIUyrRXOV21FeYFq6xGt9i+KBYmcmmJAdulRBoIzATtwhxwK9t2fWeZwmeAqcOHD2Pw4F1QijF66STOf3yuwdSSYqrT7aHX66HdbmPfgQMoiuKawtSlmQ0v6lFTDAN6Cm+YkLaJj9DtdjAcrqDT1V5OkzTB9tYWppMJlCpch/nMamyehRVMpUoslU7mRQCxWGqoByw7dBv34kRzqikVn1weZXmEz1Qne6jzHoAk+wpAhVM4elkrkAchi7SLNIlMmVX+Y5Iq5FmO6WSMOI7QbrfRaXfQ6/fAYGSq3lqoWo4Hn/gjrkKg1wkaelGV7QpLo936vTVh1dstLO1bsgElCJcPUwAhSRNsbW42mFpqTE0Qx7HBVPuaw9QuBhQOOo7hO6uctf/AB7BSUKzArNCNO1h76F4cOHAAURQjywpMJlO898+vQanMfXjbTbAflcg1CDv2VVp9hnM5rYACBZQqdDnKUDHtDc6rvWCPnim57U6CxZGLB4bZYVxicqXWIfF/TQuHeiD719xTwVJJfdvYD61BFhT8cRlwOT8WaRhQUNh47g10/vIBxK0YURxj35/9Popn39A+oOxaeElemSeXn1F4g2wE8x1BFB9kpAmXaFF3oJTpY7NUo4igFIFQAKHx0JKFy4OpXq+PtbU1RFGM6atnsLm5iXMfnWswheXF1Gi0g06vg7gVI44jDAYDPUu5RjBF9Y7CmtCEJjShCU24tLA7CtOEJjShCU1owkVCM6A0oQlNaEITLktoBpQmNKEJTWjCZQnNgNKEJjShCU24LKEZUJrQhCY0oQmXJTQDShOa0IQmNOGyhP8GTv9GdELhdk8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.show_results(max_n=6, figsize=(7,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Natural language processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is all of the code necessary to train a model that can classify the sentiment of a movie review better than anything that existed in the world just five years ago:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.594912</td>\n",
       "      <td>0.407416</td>\n",
       "      <td>0.823640</td>\n",
       "      <td>01:35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.268259</td>\n",
       "      <td>0.316242</td>\n",
       "      <td>0.876000</td>\n",
       "      <td>03:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.184861</td>\n",
       "      <td>0.246242</td>\n",
       "      <td>0.898080</td>\n",
       "      <td>03:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.136392</td>\n",
       "      <td>0.220086</td>\n",
       "      <td>0.918200</td>\n",
       "      <td>03:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.106423</td>\n",
       "      <td>0.191092</td>\n",
       "      <td>0.931360</td>\n",
       "      <td>03:15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test')\n",
    "learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)\n",
    "learn.fine_tune(2, 1e-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predictions are done with `predict`, as for computer vision:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "('pos', tensor(1), tensor([0.0041, 0.9959]))"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.predict(\"I really liked that movie!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tabular"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building models from plain *tabular* data is done using the same basic steps as the previous models. Here is the code necessary to train a model that will predict whether a person is a high-income earner, based on their socioeconomic background:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.372298</td>\n",
       "      <td>0.359698</td>\n",
       "      <td>0.829392</td>\n",
       "      <td>00:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.357530</td>\n",
       "      <td>0.349440</td>\n",
       "      <td>0.837377</td>\n",
       "      <td>00:06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = untar_data(URLs.ADULT_SAMPLE)\n",
    "\n",
    "dls = TabularDataLoaders.from_csv(path/'adult.csv', path=path, y_names=\"salary\",\n",
    "    cat_names = ['workclass', 'education', 'marital-status', 'occupation',\n",
    "                 'relationship', 'race'],\n",
    "    cont_names = ['age', 'fnlwgt', 'education-num'],\n",
    "    procs = [Categorify, FillMissing, Normalize])\n",
    "\n",
    "learn = tabular_learner(dls, metrics=accuracy)\n",
    "learn.fit_one_cycle(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recommendation systems"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Recommendation systems are very important, particularly in e-commerce. Companies like Amazon and Netflix try hard to recommend products or movies that users might like. Here's how to train a model that will predict movies people might like, based on their previous viewing habits, using the [MovieLens dataset](https://doi.org/10.1145/2827872):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1.497551</td>\n",
       "      <td>1.435720</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1.332337</td>\n",
       "      <td>1.351769</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1.180177</td>\n",
       "      <td>1.046801</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.913091</td>\n",
       "      <td>0.799319</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.749806</td>\n",
       "      <td>0.731218</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.686577</td>\n",
       "      <td>0.715372</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>0.665683</td>\n",
       "      <td>0.713309</td>\n",
       "      <td>00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = untar_data(URLs.ML_SAMPLE)\n",
    "dls = CollabDataLoaders.from_csv(path/'ratings.csv')\n",
    "learn = collab_learner(dls, y_range=(0.5,5.5))\n",
    "learn.fine_tune(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the same `show_results` call we saw earlier to view a few examples of user and movie IDs, actual ratings, and predictions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>movieId</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.985477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.629225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>91.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.476280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>48.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.043919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>75.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.023057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>42.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.509050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>40.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.686552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>63.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.862713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>32.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.356578</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.show_results()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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